130103 final report - rise of the machines ritc view final jan 2013

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Rise of the Machines? Adoption of automation technology in the Australian resources industries

and its implication for vocational education and training and higher education

November 2012

Rise of the Machines? Adoption of Automation and Remote Control Technologies In the Australian Resources Industries and Implications for Training and Higher Education

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Disclaimer

This document has been prepared by Australian Venture Consultants Pty Ltd (ACN: 101 195 699) (‘AVC’). AVC

has been commissioned to prepare this publication by the Resources Industry Training Council (RITC) and has

received a fee from the RITC for its preparation.

While the information contained in this publication has been prepared by AVC with all reasonable care from

sources that AVC believes to be reliable, no responsibility or liability is accepted from AVC for any errors,

omissions or misstatements however caused. Any opinions or recommendations reflect the judgment and

assumptions of AVC as at the date of the document and may change without notice. AVC, its officers, agents and

employees exclude all liability whatsoever, in negligence or otherwise, for any loss or damage relating to this

document to the full extent permitted by law. Any opinion contained in this publication is unsolicited general

information only. AVC is not aware that any recipient intends to rely on this document or of the manner in which a

recipient intends to use it. In preparing this information it is not possible to take into consideration the information

or opinion needs of any individual recipient. Recipients should conduct their own research into the issues

discussed in this document before acting on any recommendation.


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Acknowledgements

The analysis that forms the basis of this report was in part reliant on input and insights from a range of

automation and resources industry technology experts, operational managers and resources sector training

and education experts.

The authors thank the following individuals for their invaluable contributions to this report:

Timothy Berryman, Mine Technical Services Manager, KCGM

David Cavanagh, Managing Director, Integrated Energy Pty Ltd

Adrian Clement, Technology Manager, Westrac

Professor John Dell, Dean, University of Western Australia Faculty of Engineering

Peter Ebell, Executive Director, Engineering Technology and Business, Central TAFE

Greg Guppy, Director, Applied Engineering, Challenger TAFE

Peter Henderson, Principal Electrical Engineer, Xstrata Coal

Matt Hollamby, Brisbane Manager, Terminals Division, Patrick Corporation

Professor Hugh Durrant-Whyte, (former) Research Director, Australian Centre for Field Robotics,

University of Sydney

Simon Hehir, Principal Development Engineer, Woodside Energy

Derek Hunter, CEO, Kinetic Group

Jill Jameison, General Manager, Training Services, Challenger Institute of Technology

Neil Kavanagh, Chief Science and Technology Officer, Woodside Energy Limited

Bill Knight, Manager of Mines, Alcoa World Alumina Australia

Peter Knights, Executive Director, Mining Education Australia

Michael Lehman, General Manager, Westrac Institute

Peter Lilly, Senior Manager, Research and Development, BHP Billiton

Ross McAree, Director, CRCMining

Rudrajit Mitra, Director – Undergraduate Studies, School of Mining Engineering, University of New

South Wales

Fred Pearce, Installation Coordinator, Woodside Energy Limited

Peter Wilson, former Business Development Manager, Patrick Stevedoring


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CONTENTS

Executive Summary ................................................................................................................................................ 8

Introduction and Background ............................................................................................................................... 19

The Australian Resources Industry: An Overview ................................................................................................. 20

Automation Technology and The Resources Industry .......................................................................................... 23

Automation Technology and Its Components .................................................................................................. 23

Definition of Automation, Remote Control and INtegrated Operations ...................................................... 23

What Are the Key Technologies Used in Automation Systems? .................................................................. 24

Other Characteristics of Resources Industry Automation Systems .............................................................. 30

The Evolving Challenge for the Resources Industry Workforce ................................................................... 32

Key Centres of Excellence in Resources Industry Automation and Robotics ............................................... 33

The Adoption of Automation in the Australian Resources industries .................................................................. 40

A Framework for Assessing the Dynamics of Innovation Adoption.................................................................. 41

Factors that Determine the Rate and Extent of Adoption of an Innovation ................................................ 41

The Market For New Innovations ................................................................................................................. 42

Adoption of Automation in Other Industries .................................................................................................... 43

Case Study: Automated Port Conatiner Terminals ....................................................................................... 44

Case Study: Automation and Agriculture ..................................................................................................... 51

Is Automation a Compelling Solution for Port Freight Terminals and Agriculture? ..................................... 54

General Drivers of Adoption of Automation in the Resources Industry ........................................................... 56

Improved Productivity .................................................................................................................................. 57

Improved Resource Access ........................................................................................................................... 63

Occupational Health and Safety ................................................................................................................... 64

Reduced Reliance on Conventional Resources Industry Labour Markets .................................................... 64

Reduced Environmental Externalities ........................................................................................................... 65

Detractors To Adoption of Automation in The Australian Resources Industry ................................................ 65

Higher Capital Investment and Impact on Project Economics and Switching Costs ..................................... 66

Technological Uncertainty ............................................................................................................................ 67

Organisational Change .................................................................................................................................. 67

New Operational Risks .................................................................................................................................. 69

Planning for Automation .............................................................................................................................. 69


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Australian Resources Industry and Adoption of New Technology ................................................................... 69

Minerals Industry .......................................................................................................................................... 70

Oil and Gas Industry...................................................................................................................................... 71

Status and Trajectory of Adoption of Automation in Specific Operation Types and Sectors that Comprise the Australian Resources Industry .......................................................................................................................... 73

Type of Resources Operation ....................................................................................................................... 74

The Case for Adoption of Automation in Specific Sectors – Some Examples ............................................... 79

Automation and Workforce Structure .................................................................................................................. 85

The Impact of Automation on New Skills Requirements, Organisational Culture and Workforce Structure ...................................................................................................................................................................... 85

The Automation Technician .......................................................................................................................... 86

Mechatronics Engineer ................................................................................................................................. 90

Production Managers and Process Optimisation Experts ............................................................................ 91

The Market for New Resources Industry Automation Roles ........................................................................ 91

Implications for Vocational Education and Training ............................................................................................. 93

Vocational Education and Training Programs ................................................................................................... 93

Central TAFE – Diploma in Engineering – Technical (Mechatronic).............................................................. 94

Challenger TAFE – Australian Centre for Energy and Process Training ........................................................ 96

Charles Darwin Univeristy ............................................................................................................................ 99

Central Queensland University ................................................................................................................... 100

Westrac Institute ........................................................................................................................................ 101

Implications for Higher Education ...................................................................................................................... 103

Current University Engineering Programs ...................................................................................................... 104

University of Western Australia .................................................................................................................. 104

Curtin University ......................................................................................................................................... 107

University of Queensland ........................................................................................................................... 109

University of New South Wales .................................................................................................................. 112

University of Sydney ................................................................................................................................... 114

Programs for Production Process Optimisation manager .............................................................................. 115

Appendix 1: Automation Technician Tasks ......................................................................................................... 117


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Table of Figures

Figure 1 - Gross Value of Australian Resources Production by State (2008-09) ................................................... 20

Figure 2- Estimated Capital Cost of Advanced Minerals, Energy and Related Infrastructure Projects by State

(2011).................................................................................................................................................................... 21

Figure 3 - The Resources Industry Automation Continuum ................................................................................. 24

Figure 4 - Networking Hierarchy ........................................................................................................................... 28

Figure 5 - A Typical Remote Operations Centre ................................................................................................... 32

Figure 6 - The Key Challenge Presented by Automation ...................................................................................... 33

Figure 7 – Segmentation of the Market for New Innovations .............................................................................. 42

Figure 8 - Western Australian Rural Land Values 1981 - 2005 (Selection Regions) .............................................. 53

Figure 9 - Extent of Adoption of Automation in the Livestock, Cropping and Port Container Terminal Industries

.............................................................................................................................................................................. 56

Figure 10 - General Drivers of a Decision to Adopt Automation in the Resources Industry ................................ 57

Figure 11 – Multifactor Productivity Growth 1974-75 to 2006-07: Resources Industry versus Other Sectors of

the Australian Economy ........................................................................................................................................ 62

Figure 12 - General Detractors to a Decision to Adopt Automation in the Resources Industry ........................... 66

Figure 13 - Historical Adoption of Certain Underground Mining Technologies by the Australian Mining Industry

.............................................................................................................................................................................. 71

Figure 14 - Technology Development in the Oil and Gas Industry ....................................................................... 72

Figure 15 - Progressive Depth of Petrobas Wells in Offshore Brazil ..................................................................... 73

Figure 16 - Development of Subsea Processing Technology ................................................................................ 79

Figure 17- Support Required by the Automation Technician Role Today ............................................................ 88

Figure 18 - Support Required by the Automation Technician Role within 15 Years............................................. 89

Figure 19 - Certificate III Engineering - Technical Program - Central TAFE ........................................................... 95

Figure 20 - Diploma in Engineering – Technical (Mechatronics) .......................................................................... 96


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Table of Tables

Table 1 - Sensor Technologies Applicable to Resources Industry Automation .................................................... 26

Table 2 - Networking Technologies Applicable to Resources Industry Automation ............................................ 29

Table 3 - Mechatronics Technologies Applicable to Resources Industry Automation ......................................... 29

Table 4 - Major Research Themes at the Australian Centre for Field Robotics .................................................... 35

Table 5 - CRC Mining Partners .............................................................................................................................. 36

Table 6- Application of Automation in the Agricultural Industry ......................................................................... 52

Table 7 - Factors Influencing the Adoption of Automation in the Port Freight Terminal and Agricultural

Industries .............................................................................................................................................................. 55

Table 8 - Factors that Contribute to Decreasing Quality of Minerals and Petroleum Resources ......................... 59

Table 9 - Current Skills Requirements of an Automation Technician ................................................................... 87

Table 10 – Automation Technician Soft Skill Requirements ................................................................................. 90

Table 11- Australian Centre for Energy and Process Training Process Operations Programs .............................. 98

Table 12 – Example of VET Course Structure at Charles Darwin University – Diploma of Engineering and

Associated Degree in Process Engineering ......................................................................................................... 100

Table 13 - University of Western Australia - Mechanical, Electrical and Electronics and Mechantronics

Engineering Course Content ............................................................................................................................... 106

Table 14 - University of Western Australia - Mining, Petroleum and Mechatronics Engineering Course Content

............................................................................................................................................................................ 107

Table 15 - Curtin University Mechanical, Electronic and Communication and Mechatronics Engineering Course

Content ............................................................................................................................................................... 108

Table 16 – Curtin University Mining, Petroleum and Mechatronics Engineering Course Content .................... 109

Table 17 - University of Queensland Mechanical, Electrical and Mechatronics Engineering Content ............... 110

Table 18 - University of Queensland Mining and Mechatronics Engineering Course Content .......................... 112

Table 19 - University of New South Wales Mechanical, Electrical and Mechatronics Engineering Content ...... 113

Table 20 – University of New South Wales Mining, Petroleum and Mechatronics Engineering Course Content

............................................................................................................................................................................ 114

Table 21 - University of Sydney Mechatronics Engineering Course Content ..................................................... 115


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EXECUTIVE SUMMARY

Background

The Resources Industry Training Council’s primary purpose is to provide strategic advice to the Western

Australian State Training Board and the Department of Training and Workforce Development regarding the

development and implementation of innovative solutions to address skills shortages and the changing

workforce needs of the Western Australian resources industries.

In 2011 the Australian resources industry exported minerals and energy commodities with a total value of

A$190 billion. Australia is in the top five producers of most of the world’s key mineral commodities. While

Australia’s vast and diverse natural resources endowment has underpinned this world-class industry, as with

resources industries world-wide, it has been technological advancement in exploration, production and

processing methods that has resulted in Australia being one of the world’s most important and advanced

resources industries.

As the Australian resources industries expand in response to unprecedented and likely sustained demand for

commodities from the growing economies of the developing world, issues of improved productivity, labour

market constraints, OH&S, and access to resources that increasingly present significant technical,

environmental and social challenges are strategic and operational issues that are ‘front-of-mind’ for resources

company executives. A component of the solution to addressing each of these issues resides in the

development and implementation of remote controlled and automated systems that improve both capital and

labour productivity, remove humans from harmful or dangerous environments and reduce the externalities

that result from resources operations.

The increasing implementation of remotely controlled and automated systems in resources industry

operations, either incrementally or on a step-change whole of operation basis, has implications for workforce

structure, skills requirements, organizational structure and culture, and ultimately, the vocational education

and training (VET) and higher education programs and qualifications that provide the industry with an

appropriately skilled workforce.

The Key Issue: A Workforce that Supports New Technologies and a New Operating Environment

Automation can be broadly defined as the intelligent management of a system, using appropriate technology

solutions, so that operations of that system can occur without direct human involvement.1 The term

automation is used somewhat clumsily in industrial applications to describe systems and processes that are

characterized by a range of direct human involvement intensity, including processes and systems that have

high levels of human involvement through remote control. It is also used to describe the application of

information and communication technologies to achieve integrated operations.

1 Mining Industry Skills Centre (2010), Automation for Success


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For the purposes of this report, the term automation is used to describe automated and remotely controlled

systems as well as the application of information and communications technologies to effect integrated

operations.

Automation involves a system of integrated technologies, analytical and processes logic software that

intelligently perform a function within a discrete process, across an entire process or across an entire system.

Specific technologies that typically comprise an automation system in a resources industry operation include:

Sensor technologies

Database and data fusion technologies

Logic software technologies

Visualisation and simulation technologies

Collaboration technologies

Networking technologies

Mechatronic technologies

Automated systems in a resources industry operation involve field robotics technology, high levels of

‘ruggedisation’ and/or ‘marinisation’, and for mission critical and high OH&S risk tasks, very high levels of

systems reliability.

Perhaps the most important aspect of automated mining and petroleum production systems is that it creates

the opportunity to centralize the monitoring and control of all the processes that comprise the operation to a

single physical location. The ability to locate some front-line workers to a central, and increasingly remote,

Operations Centre (OC) where they can apply their knowledge to analyzing and interpreting operational data

streams from sensors attached to equipment in the field, historical and real-time operational data from across

the operation, and other third party data sets, creates a decision environment for effective and efficient

problem solving, and opportunities to optimize operations that has not previously existed in many sectors of

the resources industry

They challenge that automation presents to the resources industry, particularly the mining industry, is that the

current conventional resources industry workforce does not support the new technologies that are being

deployed or the integration of those technologies and the skills, work patterns, leadership models and culture

of a typical resources operation is not designed to achieve the optimisation benefits that can accrue from an

integrated approach to operations management. This is illustrated conceptually in the figure below.


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Adoption of Automation by the Australian Resources Industry

The current level of adoption of automation in the resources industry exists on a continuum spanning from the

gradual implementation of off-the-shelf technologies to various aspects of operations (nominal automation),

to almost total automation and remote control of discrete stages of the production process (partial

automation), to mining and petroleum operations that involve very high levels of automation of the process

from extraction to market delivery.

As automation systems move along this continuum in the resources industry, the extent of current adoption

decreases (more profoundly in the minerals industry than in the petroleum industry). Typically, the proprietary

nature of intellectual property associated with the automation system increases, as does the need for new

skills and structural and cultural change in the organization to support the automated environment and

optimize its benefits through putting into effect integrated operations. This is illustrated conceptually in the

figure below.

Main Implication for the Resources IndustryWorkforce

Sensor Technologies

Database and DataFusion Technologies

Logic Software

Visualisation &Simulation Technologies

NetworkingTechnologies

MechatronicsTechnologies

GPS, Precision GPS, mmRadar, Scanning Laser Range Finder,Infrared Spectrometer, StrainGauges, Resolver and Encoders,LVDT Sensors, Intertial Sensors,RFID etc

PLCs. Embedded PCs, multi-Core computers etc

2D & 3D media, virtual reality etc

Predictive software that determineslikely whole-of-operations outcomesfor a set of actions

Internet, satellite, microwave,fibre optics, communicationsProtocols etc

Electric Drive Systems, Hydraulic Drive Systems, Robotic Task Allocation, SCADA Control etc

Field robotics

Storage and interrogation of vastQuantities of data

Code that facilitates the integrationand interrogation of hetrogenousdata sets

CollaborationTechnologies

Video, audio and data connectivitybetween mobile devices and devicesIn fixed locations

Operations CentreSystems that facilitate the monitoringand control of the entire operationfrom a single central location

Many of these technologies,and the integration of these

technologies is not supportedby a conventional resources

industry workforce ororganisational culture


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Estimating the extent and rate at which automation will be adopted across the many different sector and

operations types that comprise the Australian resources industry is difficult. This is because there is a

tremendous amount of variety in strategy, operational layout, upstream and downstream integration, OH&S

issues, environmental issues and general suitability to various degrees of automation across the many

operations that comprise each sector of the Australian resources industry, rendering the degree to which

automation is compelling to specific operations complex and multifaceted.

Generally speaking, the principal factor that drives a decision to adopt automation relates to addressing the

following unique factors associated with improving productivity in the resources industry:

The resource Depletion Effect

Mineral and hydrocarbons have a unique aspect as a natural resource – they are non-renewable.

Because commercial enterprises are motivated to extract the highest quality resources first, as these

resources are extracted, the quality that remains in-situ decreases. This means there needs to be a

concomitant increase in productivity for resources operations to remain viable.

Cost of Labour

Resources industry workers generally receive higher remuneration packages than many other

industries. This is reflective of the specialised nature of the work and the hardships, including working

in isolated environments, that are associated with many roles. On-costs associated with resources

industry staff are also typically higher than with those associated with other industries by virtue of the

additional costs associated with transferring and accommodating staff at remote locations.

Nominal AutomationAutomation of an individual

device or systems component

E.g. Remotely operated equipment

Off-the-shelf solutions

Partial AutomationSubsystem operated by a

control room

E.g. Milling circuit that is operated via a central control

room

Off-the-shelf solutions with some proprietary design

Total AutomationFully integrated, automated and

remote controlled extraction, processing and logistics

operation

E.g. Rio Tinto Future Mine

Large component of proprietary design

Degree ofAutomation

RelativeLevel of

Adoption

IntellectualProperty

High

Low

Minerals Petroleum

High

Low

Minerals Petroleum

High

Low

Minerals Petroleum

Minimal Some Significant

Need forNew Skills

and Culture


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Automation addresses the cost of labour by improving the productivity of labour, and potentially

reducing the number of staff required on remote sites.

Capital Effect

Resources projects are capital intensive. Furthermore, there are long lead-times between final

investment decision for a project and when the capital actually becomes productive. This has a

negative effect on project Net Present Value. Automation addresses this by increasing the

productivity of the capital once it is operational.

Automation also improves productivity by facilitating integrated operations, which provides opportunity for

whole-of-operation optimisation, and by allowing more predictable maintenance planning and scheduling.

There are other drivers of automation that are linked to improving productivity, but which also deliver other

benefits including improved resource access, reduced reliance on conventional resources industry labour

markets, reduced negative environmental externalities and improved OH&S. The general drivers of a decision

to implement automation are summarised in the figure below.

As there are general drivers of a decision to adopt automation in the resources industry, there are also general

detractors to that decision. Principally, these are a set of related factors that potentially have a negative

impact on project finance and/or operational risk. The general detractors to a decision to implement

automation are summarised in the figure below.

Productivity

Resource DepletionEffect

Cost of Labour Capital Effect Whole of OperationsOptimisation

Maintenance

Automation counters thenegative effect on productivity caused bya decreasing quality ofin-situ resources

Labour costs in theresources industries arehigh and automation improves the productivityof labour

Resources projects arecapital intensive and subject to long productionlead times. Automationimproves the productivityof capital

Automation providesproduces enormousamounts of operationaldata that can be used tooptimise operations

Automation may notreduce the amount ofmaintenance requiredbut may improve thepredictability of maintenance scheduling

Improved ResourceAccess

Reduced Reliance onConventional Resource Industry Labour Markets

Reduced NegativeEnvironmental Externalities

Improved OH&S

Automation facilitates accessto resources in environmentsthat cannot be safely accessedby manned equipment

The change in job functions andlocation that results fromautomation provides access toa more diverse employmentmarket

Automation facilitates moreprecise operation leading to decreased energy consumptionand smaller operational footprint

Automation removes peoplefrom dangerous operatingenvironments


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Despite the entire resources industry sharing these common drivers and detractors, the oil and gas industry

has been a far more rapid implementer of new technology than the minerals industry. The higher propensity

for the oil and gas industry to invest in technology development and deployment has most likely been a result

of the more rapid depletion of its global resources, and the need to develop technology that enables entry into

significantly more challenging exploration, production and processing frontiers and the more globally

integrated nature of the oil and gas industry’s supply chain.

While the case for adoption of automation is most certainly company and site specific, we can make some

slightly more specific observations at a resources operations type and resources sector level. The figure below

summarises current adoption of specific automation technologies and the likely next phase of automation

implementation for different resources operations types.

Impact on ProjectEconomics

Impact of higher capital cost on NPVfor greenfields projects

Impact of switching costs on NPV forbrownfields projects

Technology RiskMany new technologies that haven’tbeen extensively trialled in resourcesindustry applications

Risk associated with equipment andautomation OEM support integration

New OperationalRisks

Over-reliance on automated processes

Passive operator risk

Over-reliance on systems redundancyapproach of OHS

Organisational Change

New roles and work patternsMulti-site integrationNew modes of communicationNew reward systemsWorkforce retrainingNew leadership models

Project Finance Risk

Operational Risk

Operational Risk


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Similarly, more specific observations can also be made with respect to the status of adoption and specific

issues facing adoption of automation for sectors of the resources industry. To date, the adoption of

automation within the mining industry has been most prolific in the bulk commodity sectors, particularly with

respect to iron ore and coal, with adoption across other sectors being more sporadic. While the case seems

adequately compelling for large complex iron ore and coal operations, it is less so for bauxite operations, and

highly variable across other sectors. This is illustrated conceptually in the figure below.

Minerals Exploration Offshore O&G Exploration

Open Pit Mining Underground Mining

Platform, FPSO, FLNG Production Subsea Production & Processing

Current Automation:• Processing of remote

sensing data

• UAVs for dataacquisition

Next Phase?• Automation of drill rig

operations

• Automated real-timeassaying

Current Automation:• Automated systems onexploration platforms

Next Phase?• Automation processing ofseismic and other

geophysical data forfaster turnaround

Current Automation:• Loaders that operate from

blast block data• Haulage

Next Phase?• Loaders that operate from

bucket sensors• Drilling and blasting

Current Automation:• LHDs• Haulage• Long-wall miners• High-wall miners

Next Phase?• Continuous miners• Tunnel developers• Bolting and meshing

Current Automation:• Normally unmanned

production platforms

• FPSOs and FLNG involvehigh levels of automation

• ROVs• ROCs

Next Phase?• Still over 1,000 operationsthat are performed manually

in a state-of-the-art petroleum system

• Limited scope for processvariation

Current Automation:• High levels of automationby necessity

• Reliability of processes issuper-critical

Next steps?:• Pre-programmed IMRROVs


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Because the case for automation is not equally compelling across all styles of operation or sectors that

comprise the Australian resources industry, the adoption of automation by the Australian resources industry is

likely to be sporadic and incremental in most cases, rather than the rapid transformation that is sometimes

predicted.

Automation and Workforce Structure

As automation is progressively adopted by the resources industry, new technologies will be deployed that are

not supportable by the current resources industry workforce skill base, particularly in the case of the minerals

industry. The culture of operations that adopt extensive automated systems will change dramatically, again,

particularly in the case of the minerals industry. The new culture will be one that is based on a higher

incidence of remote control, workforce diversity and integrated, multidisciplinary, data rich problem solving.

There is no doubt that automation will render certain roles in resources operations redundant as it has in

other industries. However, there is little evidence to suggest it will result in significant reduction in overall

employee numbers. Obvious candidates for redundancy are operators of the equipment that becomes

automated, such as drill rigs, loaders, haul trucks and trains. However, even in these obvious cases, some of

that workforce will most likely be retrained to operate equipment or sets of equipment remotely, and to

oversee components of the automated system. Some unskilled and semi-skilled roles may also be replaced by

automation.

The event of automation is unlikely to result in a significant reduction of tradespersons that are employed on a

conventional resources operation, as most of the technical issues addressed by tradespersons will remain. For

example, while automated equipment may be designed for a higher incidence of ‘change-out’ style

Underground Coal Industry Iron Ore

Alumina-Bauxite Other Sector

Automation Development ProgramsSignificant industry collaboration with research organisationsthrough Australian Coal Association Research Program

Primary ApplicationsPrimarily around long-wall operationsHigh-wall mining is also highly automated

BenefitsAutomated long-wall shearer face alignment and retreat hasresulted in significant productivity improvementOH&S benefits

Automation Development ProgramsIndividual company collaborations with equipment OEMs andresearch organisations

Primary ApplicationsTotal value chain automation (‘blasting to port’)Fundamentally, automation of complex logistics exercise

BenefitsSignificant improvements in productivity only attributable tolarge, multi-mine operationsOH&S benefitsLabour market benefits

Automation Development ProgramsIndividual company collaborations with OEMs

Primary ApplicationsHaulage only as haulage routes are long, but mining iscomplicated by significant vertical grade variation anddownstream processes are already highly automated

BenefitsLimited because mining is a relatively small portion of the totalcost of producing alumina

Complicated by significant diversity in a range of factorsIncluding:

• Physical scale• Throughput• Mine life• Ratio of mining cost to total costs• Production goals

• Operational layout• Type of mining process• Degree of OH&S risk that can be mitigate by automation


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maintenance where malfunctioning components are removed and sent off for repair and replaced by a spare

component on site, there is already a high incidence of this style of maintenance in modern resources industry

equipment. Routine mechanical issues such as oil leaks will still require maintenance attention on site.

Increased automation may result in an increase in the number of electrical tradespersons required on site to

support change-outs and other ICT systems. However, different demands from tradespersons will most likely

be best addressed through modifications to trade qualifications and additional training. The removal of driver

error may result in improved predictability of maintenance scheduling.

While the precise impact of automation on workforce size and structure is not entirely clear, there is general

consensus among operators that the following three roles that are not usually associated with resources

industry, particularly mining operations, but are commonplace in other automated environments, will become

increasingly important operational roles in the resources industry:

Automation Technician

The role of an automation technician is to build, install and maintain automated machinery and

equipment. It is largely a systems integration role, with electrical tradespersons still being required to

perform functions such as wiring and mechanical tradespersons still required to address mechanical

issues. If deployed on an operating environment today, it is expected that an Automation Technician

would be heavily reliant on support or direction from other experts (engineers and tradespersons) to

perform many of the tasks.

Mechatronics Engineer

Mechatronic technologies are central to field robotics and the application of automated and remote

control systems to resources industry operations. Mechatronics engineering is a multidisciplinary field

that combines electrical, mechanical, computing and software engineering to create expertise in

designing, building, deploying and maintaining electromechancial devices such as robotics. A

particular skill set that is common to mechatronics engineers that is crucial to many resources

operations automation programs is data fusion expertise. Because highly automated resources

industry operations produce enormous volumes of data from heterogeneous data streams, the ability

to write software code that can interpret and integrate those heterogeneous data streams is critical

to not only the operation of automated systems, but also optimizing their benefits.

Operations Optimisation Manager

As resources operations become more automated and the immediate benefits of the automation

program are realized, significant additional benefits can be attained through optimization, as has

been the experience of other largely manual processes that have achieved high levels of automation.

This role applies expertise in logistics and process optimization to achieve optimal whole of

operations productivity and other benefits, and is performed by an operations optimization manager.

Previous analysis has estimated that on the basis that 50 percent of the 500 resources industry sites in

Australia required 3 to 5 automation technicians, that 1,500 such roles would need to be filled. In light of the

discussion in this paper on the complexities associated with the adoption of automation in the resource

industry, it is unlikely that demand for automation technicians will emerge to this extent in the short term.

Anecdotally, it would seem that the functions of an automation technician are currently being filled by

resources companies implementing automation from two key sources:


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Electrical tradespersons who acquire the additional skills required to perform the automation

technician role through experience and some on-the-job training. It was noted from the interviews

associated with this report that this pathway will not be adequate in the longer-term because many

trade staff may struggle to attain the higher-level skills that are required for the job; and

Technicians operating in other industries that have higher-level automation related skills. In the

mining industry a significant portion of such technicians seem to be recruited from the Army, and in

the case of the oil and gas industry, from the Navy’s Submarine Service.

Implications for Vocational Education and Training

The current absence of a resources automation technician qualification is primarily the function of the

following two factors:

Absence of an immediate market

The development and delivery of courses by training and education organizations is a function of the

market demand for those courses. It is likely that there is currently not a big enough employment

market for graduates with a comprehensive set of skills in resources industry automation and as such

limited student demand. This is a function of the fact that extensive automation is currently not

widely adopted, and that where extensive automation is adopted, skills and expertise gaps are being

filled by electrical engineers, or engineers and tradespeople with automation skills that have been

developed in other industries such as defense. It is unlikely that institutions will invest in resources

industry automation programs to any great extent until there is an adequate addressable market for

the courses.

Commercial-in-Confidence nature of many automation programs

Most of the extensive automation programs that are currently being developed and deployed are

being done so by large multinational mining companies seeking first mover advantage in automation.

As such, the intellectual property associated with these programs is being treated as commercial-in-

confidence. The training of deployment and maintenance staff for these programs is typically

conducted in collaboration with an equipment OEM or under an exclusive arrangement with a specific

institution of training and/or education. This makes it difficult for other institutions to develop and

validate general resources industry automation curricula.

At a mechanical trade qualification level (Certificate III), it is possible to cover some basic electrical concepts

and to obtain a restricted electrical license. However, this is significantly deficient with respect to the skills

required of an automation technician. An electrical trade qualification covers the required electrical skills more

comprehensively including control technologies such as PLC, but still falls short of the required skill set. While a

dual trade qualification (mechanical and electrical) would substantially progress a tradesperson toward the

required qualified skill set, it will also still be deficient.

It is therefore not surprising that both public and private Registered Training Organisations are trending

toward creating a qualification for an automation technician as a post trade qualification, typically at Diploma

level, but in some cases associate degrees. There is also a view that most of the material for this post-trade

qualification could be compiled by combining content from a range of existing electrical and mechanical


18

Certificate IV and Diploma qualification curricula. Additionally, some course structures offer units in working

and communicating in different cultures, and facilitate remote delivery of the course.

Implications for Higher Education

Generally speaking, it would seem that two different pathways are possible for the training of engineers with

adequate skills and expertise to work with more automated resources industry systems:

Mechatronics Engineering in Resources Undergraduate Degree

It would seem that the main challenge that resource companies face in employing a mechatronics

engineering graduate is the lack of expertise in mining or hydrocarbon production processes

possessed by the graduate, as conventional mechanical and electrical engineering can be harnessed

by employing mechanical or electrical engineers. As such, there is a possibility that a specialised

mechatronics engineering in resources undergraduate degree may emerge. This is unlikely to

eventuate until the adoption of automation is adequately comprehensive so that a specific new

resources industry technical profession in automation emerges.

Post Graduate Qualification

In the short to medium term, it is more likely that a post-graduate qualification such as a graduate

diploma or masters degree in mechatronic engineering that is focused on developing the required

automation expertise in mechanical, electrical, mining or oil and gas engineering graduates will be the

most practical pathway for relevant formal qualifications.

The high incidence of commercial confidentiality that surrounds proprietary automation programs is making it

difficult for universities to assess future skill needs and determine the capability that needs to build into

faculties for the delivery of future programs. While some industry automation programs are working directly

with specific universities and other training organizations to develop packages for their employees, it is

unlikely that wider consultation will occur until automation is more widespread.

An analysis of Australian universities that offer programs in mechanical, electrical, mechatronic, mining and

petroleum engineering highlights the following:

Within the combined curricula at each institution there appears to be a plethora of course material

that subject to the requirements of the specific institution’s academic council and Engineers Australia,

could potentially be reconfigured to at least form the basic formal qualifications at either an

undergraduate or graduate level to meet the foreseeable technical professional needs of the

resources industry as demand dictates;

In all cases, the electrical and electronic engineering curricula most closely resembles that of the

mechatronics curricula, noting that in some cases, a limited number of subjects more typically taught

as part of a mechatronics or electrical engineering degree are also taught in the mechanical

engineering degree; and

In all cases, the content in the mining engineering and petroleum engineering curricula is the most

removed from the mechatronics degree curricula. However, at least one university is contemplating

developing an elective mechatronics stream as part of their bachelor of mining engineering program


19

INTRODUCTION AND BACKGROUND

The Resources Industry Training Council (RITC) is a Western Australian Government funded joint venture

between the Chamber of Minerals and Energy, Western Australia (CMEWA) and the Australian Petroleum and

Exploration Association (APPEA). The RITC’s primary purpose is to provide strategic advice to the Western

Australian State Training Board and the Department of Training and Workforce Development regarding the

development and implementation of innovative solutions to address skills shortages and the changing

workforce needs of the Western Australian resources industries2.

As the Australian resources industries expand in response to unprecedented and likely sustained demand for

commodities from the growing economies of the developing world, issues of improved productivity, labour

market constraints, OH&S and access to resources that increasingly present significant technical,

environmental and social challenges, are strategic and operational issues that are ‘front-of-mind’ for resources

company executives. A component of the solution to addressing each of these issues resides in the

development and implementation of remote controlled and automated systems that improve both capital and

labour productivity, remove humans from harmful or dangerous environments, and reduce the externalities

that result from resources operations.

The increasing implementation of remotely controlled and automated systems in resources industry

operations, either incrementally or on a step-change whole of operation basis, has implications for workforce

structure, skills requirements, organizational structure and culture and ultimately, the vocational education

and training (VET), and higher education programs and qualifications that provide the industry with a skilled

workforce.

This report examines:

The nature of remotely controlled and automated systems that are used in the resources industries

and the discrete technologies that comprise those systems;

The application of remote controlled and automated systems in other industries, and the issues that

have been encountered in those industries with respect to adoption and implementation within those

industries;

The current extent of adoption of various remote controlled and automation systems throughout the

value chain of different sectors of the Australian resources industry, and the current adoption

trajectory of such systems in these sectors;

Changes in workforce structure, skills requirements and organizational structures and cultures that

will be required to facilitate the effective adoption of remote controlled and automated systems in

resources industry operations;

The implications of any new skills requirements on VET and higher education programs, and

ultimately, the qualifications that institutions delivering these programs will need to be able to issue

so that tradespeople, technicians and technical professionals can safely and effectively deploy,

maintain and operate remotely controlled and automated resources industry systems; and

The readiness and capacity of the VET and higher education sector to deliver these qualifications to

the Australian resources industry.

2 In the context of the RITC and this report, the meaning of ‘resources industries’ is taken to include all

minerals and hydrocarbon exploration, extraction, processing and exporting activity.


20

THE AUSTRALIAN RESOURCES INDUSTRY: AN OVERVIEW

In 2011 the Australian resources industry exported minerals and energy commodities with a total value of

A$190 billion.3 Australia is in the top five producers of most of the world’s key mineral commodities. It is the

world’s leading producer of bauxite, alumina, rutile and tantalum; the second largest producer of lead,

ilmenite, zircon and lithium; the third largest producer of iron ore, uranium and zinc; the fourth largest

producer of gold, manganese and nickel; and the fifth largest producer of aluminium, diamonds, silver and

copper.4 It is currently the world’s 19

th largest producer of natural gas and 29

th largest producer of oil.

5 The

Nation’s Liquified Natural Gas (LNG) industry is set to surpass Qatar as the world’s largest exporter of LNG

within the next few years.

Exploration, production, processing and/or export activities for minerals and/or hydrocarbons occur in every

State and territory of Australia. However, minerals and petroleum operations in the states of Western

Australia and Queensland collectively account for around 75 percent of the total value of the Australian

resources industry’s output. This is illustrated in Figure 1 below.6

Figure 1 - Gross Value of Australian Resources Production by State (2008-09)

3 Bureau of Resources and Energy Economics (2011), Resources and Energy Statistics: December Quarter 2011,

Australian Government, Canberra 4 Minerals Council of Australia (2010) The Australian Minerals Industry and the Australian Economy

5 British Petroleum (2011), BP Statistical Review of World Energy: June 2011, British Petroleum, United

Kingdom 6 Bureau of Resources and Energy Economics (2011), Resources and Energy Statistics 2011, Australian

Government, Canberra

$-

$10,000

$20,000

$30,000

$40,000

$50,000

$60,000

$70,000

$80,000

Western Australia

Queensland New South Wales

Northern Territory

Victoria South Australia

Tasmania

AU

D m

illio

ns

Gross Value of Australian Resources Production by State (2008-09)


21

In 2010-11 the Australian resources industry spent A$5.9 billion on exploration. Approximately 60 percent of

this expenditure represents brownfields exploration (exploration around existing or known deposits)7 and the

majority of exploration expenditure is associated with exploration for hydrocarbons, reflecting the much

higher costs associated with offshore exploration activity.

In real terms, exploration expenditure in 2010-11 is expected to be the highest on record and nearly double

the average exploration expenditure of the past 30 years,8 albeit this is, at least in part, the result of higher

exploration costs.

Both the minerals and oil and gas sectors of the industry are in the midst of an unprecedented period of

expansion. As at the end of April 2011, there were 94 minerals and oil and gas projects at an advanced stage of

development with an associated record capital expenditure totaling A$173 billion.9 Again, the majority of this

activity is occurring in the states of Western Australia (63 percent of capital expenditure) and Queensland (28

percent of capital expenditure). This is illustrated in Figure 2 below.

Figure 2- Estimated Capital Cost of Advanced Minerals, Energy and Related Infrastructure Projects by State (2011)

In Western Australia expansion is being driven primarily by major investment in natural gas developments in

offshore Western Australia and associated onshore processing and export facilities, as well as a number of new

7 New, R., Ball, A. and Copeland, A. (2011), Minerals and Energy Major Development Projects – April 2011

Listings, Australian Bureau of Agricultural and Resource Economics and Sciences, Australian Government, Canberra 8 New, R., Ball, A. and Copeland, A. (2011), Minerals and Energy Major Development Projects – April 2011

Listings, Australian Bureau of Agricultural and Resource Economics and Sciences, Australian Government, Canberra 9 New, R., Ball, A. and Copeland, A. (2011), Minerals and Energy Major Development Projects – April 2011

Listings, Australian Bureau of Agricultural and Resource Economics and Sciences, Australian Government, Canberra

$-

$20,000

$40,000

$60,000

$80,000

$100,000

$120,000

Western Australia

Queensland New South Wales

Victoria Northern Territory

South Australia

Tasmania

AU

D m

illio

ns

Estimated Capital Cost of Advanced Minerals, Energy and Related Infrastructure Projects by State

(2011)


22

iron ore mines and logistics operations and expansion programs for existing iron ore mines and logistics

operations. In Queensland, growth is being driven primarily by new coal projects, logistics operations and the

expansion of existing coal projects and logistics operations, as well as the State’s rapidly growing coal seam gas

industry. However, there are advanced projects in a wide range of commodities across Australia.

While Australia’s vast and diverse natural resources endowment has underpinned this world-class industry, as

with resources industries world-wide, it has been technological advancement in exploration, production and

processing methods that has resulted in Australia being one of the World’s most important and advanced

resources industries. It is this technological advancement that has allowed the Australian industry to

competitively exploit resources that are increasingly being found only in complex and deep geologies,

demonstrate challenging mineralogies or reservoir characteristics, need to be accessed from challenging

terrain or deep water and need to be developed in areas that are characterized by environmental or social

conflicts. In this context, the increasing prevalence of remote controlled and automated systems in some

sectors of the Australian resources industry is no more than a continuation of this trend.


23

AUTOMATION TECHNOLOGY AND THE RESOURCES INDUSTRY

AUTOMATION TECHNOLOGY AND ITS COMPONENTS

DEFINITION OF AUTOMATION, REMOTE CONTROL AND INTEGRATED OPERATIONS

Automation can be broadly defined as the intelligent management of a system, using appropriate technology

solutions, so that operations of that system can occur without direct human involvement.10

The term

automation is used somewhat clumsily in industrial applications to describe systems and processes that are

characterized by a range of direct human involvement intensity, including processes and systems that have

high levels of human involvement through remote control. There are very few truly fully automated industrial

processes. Indeed, for many processes full automation is not desirable for reasons associated with complex

and sometimes partially subjective judgments that are required to ensure optimum efficiency, accuracy and

safety performance of a process.

Automation is also often used to describe integrated operations. The term integrated operations refers to the

integrated management of people, work processes and technology through the sophisticated application of

information and communications technologies to optimize operations. It facilitates the use of real-time data,

collaborative techniques and multiple expertise across disciplines, organizations and geographical locations.11

For the purposes of this report, the term automation is used to describe automated and remotely controlled

systems as well as systems that support integrated operations.

The current level of adoption of automation in the resources industry exists on a continuum spanning from the

gradual implementation of off-the-shelf technologies to various aspects of operations (nominal automation),

to almost total automation and remote control of discrete stages of the production process (partial

automation), to mining and petroleum operations that involve very high levels of automation of the process

from extraction to market delivery.

As automation systems move along this continuum in the resources industry, the extent of current adoption

decreases (more profoundly so in the minerals industry than in the petroleum industry). Typically, the

proprietary nature of intellectual property associated with the automation system increases, as does the need

for new skills and structural and cultural change in the organization to support the automated environment

and optimize its benefits through putting into effect integrated operations. This is illustrated conceptually in

Figure 3 below and discussed in more detail in later sections of this report.

10

Mining Industry Skills Centre (2010), Automation for Success 11

Cavanagh, D. (2012), Integrated Operations, Integrated Energy


24

Figure 3 - The Resources Industry Automation Continuum

WHAT ARE THE KEY TECHNOLOGIES USED IN AUTOMATION SYSTEMS?

Automation is not a singular technology. Rather it is a system of integrated technologies, analytical and

processes logic software that intelligently perform a function within a discrete process, across an entire

process or across an entire system. Specific technologies that typically comprise an automation system in a

resources industry operation include:

Sensor technologies

Database and data fusion technologies

Logic software technologies

Visualisation and simulation technologies

Collaboration technologies

Networking technologies

Mechatronic technologies

Technologies deployed in a typical resources industry automation system, and the automation system itself,

often require several important characteristics:

Many systems involve field robotics technologies (see later section), which are technologies that

allow highly automated pieces of mobile equipment to operate in an outdoor environment often in

the vicinity of people. This implies the need for rigorous safety features;

Nominal AutomationAutomation of an individual

device or systems component

E.g. Remotely operated equipment

Off-the-shelf solutions

Partial AutomationSubsystem operated by a

control room

E.g. Milling circuit that is operated via a central control

room

Off-the-shelf solutions with some proprietary design

Total AutomationFully integrated, automated and

remote controlled extraction, processing and logistics

operation

E.g. Rio Tinto Future Mine

Large component of proprietary design

Degree ofAutomation

RelativeLevel of

Adoption

IntellectualProperty

High

Low

Minerals Petroleum

High

Low

Minerals Petroleum

High

Low

Minerals Petroleum

Minimal Some Significant

Need forNew Skills

and Culture


25

The systems are typically deployed in harsh environmental conditions where they are exposed to the

elements (heat, dust, water etc). This implies a need for ‘ruggedisation’ or ‘marinisation’ of

technologies and systems; and

For mission critical and OH&S reasons, many automated processes in the minerals industry have to

demonstrate very high levels of reliability, and often require multiple levels of redundancy and a high

frequency of operator intervention.

The following sub sections describe some of the technologies that are common to resources industry

automation systems.

SENSOR TECHNOLOGIES

A sensor technology is a device that measures or detects a real-world condition and converts that condition to

an analog or digital representation that can be interpreted by another device or instrument or systems

software. Real-world conditions that can be measured by sensors include:

The identification, location and proximity of two-dimensional or three-dimensional physical or

biological objects ranging from nanometers in size to very large objects;

The direction and speed of motion of the device in which it is embedded or an external object;

Temperature, pressure and mass of liquid, gaseous and solid phases;

Viscosity of liquids;

Light, including the intensity of red, green or blue colour spectrums; and

Signatures of chemical entities in solid, liquid or gaseous phase.

Table 1 below describes some of the sensor technologies that are applicable to resources industry automation

systems.

.


26

Sensor Technology Description and Application

GPS Global Positioning System (GPS) is a satellite navigation system that provides location and time information in all weather, anywhere on or near the Earth’s surface where there is an unobstructed line of sight to four or more satellites. It is maintained by the United States Government and is freely accessible to anyone with a GPS receiver.

Precision GPS Precision GPS systems augment a conventional GPS algorithm by integrating other data sources and accounting for common errors to provide a high probability of precise location. Precision GPS is used by mobile automated machinery to determine position and to navigate.

mmRadar Millimetre (mm) wavelength radar is used as a sensor for the anti-collision systems on mobile autonomous equipment. It uses a very narrow pencil beam to detect the presence and speed of biological or physical objects in the pathway of the equipment.

Scanning laser range finder

Scanning laser range finders use lasers to scan an environment to create a two dimensional map of the proximity of nearby objects.

Infrared spectrometer Infrared spectrometers detect the infrared region of the electromagnetic spectrum and are used to identify chemical elements. These sensors are used to identify ore and waste in digging and loading operations.

Strain gauges Sensor measuring the strain of an object Resolvers and Encoders A resolver is an analog sensor used to measure degrees of rotation and an encoder

is a digital sensor used to measure degrees of rotation. LVDT sensors Liner Variable Differential Transformer (LVDT) sensors are used to measure linear

displacement. Inertial sensors Inertial sensors are sensors based on inertia and cover a range of sensors including

MEMS and gyroscope technologies RFID Radio Frequency Identification (RFID) use radio frequency electromagnetic fields

to transfer data from a tag attached to an object to a receiver for the purposes of identification and tracking.

Table 1 - Sensor Technologies Applicable to Resources Industry Automation

DATABASE AND DATA FUSION TECHNOLOGIES

A multitude of data is produced by automated resources equipment both from its sensors and operating logs.

Significant amounts of data are also produced through the exploration, production system design and

development phase. The ability of software to interrogate and analyse this data is central to both the

operational integrity of the automation system and optimizing its benefits.

A database is an organized collection of digital data in the form of files, records, fields and other objects. A

database management system is a software package that controls the creation, maintenance and use of a

database. Data mining and data semantic tools refer to software that allows a user to analyse and interpret

data by drawing relationships between data and analyzing those relationships. These technologies are integral

to the use of data produced by automated systems.

In a large automated system such as a resources operation, data is derived from a wide range of sources and is

rarely homogenous. Development of software code that effects the fusion of these heterogeneous data

streams is necessary to effectively analyse and interpret the data.


27

PROCESS LOGIC SOFTWARE TECHNOLOGIES

Process logic software technologies are collections of algorithms that may receive information from, sensors

and databases, and perform step-by-step problem solving computational procedures and then initiate an

action based on the outcome of that procedure. In a resources industry automation system this ranges from

relatively simple Programmable Logic Controllers (PLCs) that perform this function for a discrete action or

process, to software on embedded PCs and multi-core computers that control a number of processes in a

piece of equipment, to very sophisticated and robust software systems that control entire processes or

significant amounts of an entire operation through a very powerful integrated computing system.

VISUALISATION AND SIMULATION TECHNOLOGIES

Visualisation technologies refer to software that creates two and/or three dimensional images, diagrams or

animations to communicate information through digital media. They range from simple two-dimensional

displays to three-dimensional interactive media and virtual reality. Visualisation technologies perform a range

of functions in resources industry automation systems including facilitating accurate remote control of

processes and equipment, and supporting analysis of complex problems by operations staff.

Simulation technologies are software algorithms and associated visualization systems that predict the

outcome of an action or set of actions based on the interaction between the action and all aspects of the

operation. They determine factors such as likelihood and extent of the impact caused by the action(s), by

processing the vast amount of operational data that is generated from the automated systems. Simulation

technologies are critical to decision-making as they reduce the risk associated with a new action and facilitate

whole-of-operations optimization.

COLLABORATION TECHNOLOGIES

Collaboration technologies facilitate video, audio and data connectivity between mobile devices and devices in

fixed locations and are critical to facilitating integrated operations, as they allow mobile staff to interact deeply

with a centralized operations centre or other fixed location.12

NETWORKING TECHNOLOGIES

Networking technology refers to software and hardware that allows devices to communicate with each other.

They include wireless communications mediums such as Internet, satellite and microwave, hard wired

mediums such as copper-wire and fibre options, communications protocols and the software and hardware for

making connections and sending and receiving data. They facilitate the Local Area Networks and Wide Area

Networks that are critical for the function of automated systems.

12

Cavanagh, D. (2012), Integrated Operations, Integrated Energy


28

Competent networking presents one of the most significant technical challenges to the automation of many

mining and petroleum operations. Because these operations tend to be in remote locations, often with

significant physical distances between elements of the value chain, ensuring adequate bandwidth and

necessary connectivity reliability can be a technically challenging and capital intensive exercise. In most

resources automation applications, there is a hierarchy of connectivity reliability needs based on the OH&S

and mission critical implications of the process that requires the connectivity. This is illustrated in Figure 4

below.

Figure 4 - Networking Hierarchy

Typically, high OH&S risk, and mission critical functions are hard-wired. Sub-packages such as PLC integration

are typically hard-wired, or based on reliable wireless technology. For supervisory control and data acquisition

there is a greater tolerance for less reliable wireless technologies such as the Internet.

As wireless technologies become increasingly reliable, it is highly likely that a substitution of wireless

communications in traditionally hard-wired applications will occur, driven by the lower capital cost and greater

flexibility that is facilitated by a wireless system. There is a significant risk that in areas where there is a high

intensity of operations, such as the Pilbara and Goldfields regions of Western Australia, obtaining necessary

proprietary rights to limited frequency spectrum will become a challenge for later adopters of automated

systems.

Table 2 below describes some of the networking technologies that are applicable to resource industry

automation systems.

Significant OH&S RiskWhole of operation Mission Critical

Low OH&S RiskSubsystem Mission Critical

No OH&S RiskNon-Mission Critical

Hard-wired (copper or fibre optic)

Reliable wireless such as microwave

Range of wireless options including Internet


29

Networking Technology Description and Application

Fieldbus A family of industrial computer network protocols used for real time distributed control of complex systems

Fibre optics Optical fibre used for connecting devices through hard-wiring where communication is over long distances and/or high bandwidth is required

Wireless networks Computer and other hardware networks that are based on radio waves rather than physical cables

Radio frequency networks

Networks based on radio frequency that support technologies such as RFID

3G and 4G Systems High bandwidth digital networks that operate through the cellular telephone network

Satellite Data Networks Networks that transfer data between devices using a satellite system as the direct intermediary

Microwave Network Radio frequency based network that is typically used for point-to-point connection because the small wavelength allows conveniently-sized antennas to direct a very narrow beam that can be pointed directly at the receiving antenna allowing nearby independent networks to use the same microwave frequency without causing interference

Table 2 - Networking Technologies Applicable to Resources Industry Automation

MECHATRONICS TECHNOLOGIES

Mechatronic technologies incorporate electronic and mechanical functions into a single device to perform

robotic actions. It represents an interdisciplinary area of engineering that integrates mechanical and electrical

engineering with computer science. A typical mechatronic technology is a device that receives a signal from a

sensor, processes that signal through a software algorithm that then commands a mechanical device to

perform an action. Examples of mechatronic systems are robots, digitally controlled combustion engines,

machine tools with self adaptive tooling, contact-free magnetic bearings and automated guided vehicles.

Table 3 below describes some of the mechatronics technologies that are applicable to resource industry

automation systems.

Networking Technology Description and Application

Electric Drive Systems Actuators that use electricity to create a mechanical motion Hydraulic Drive Systems Actuators that use hydraulics to create a mechanical motion Robotic Task Allocation Software that determines the priority of specific robotic actions depending on

certain variables Robotic Task Scheduling Software that determines a schedule for the performance of various robotic

actions depending on certain variables SCADA Control Supervisory Control and Data Acquisition (SCADA) generally refers to industrial

control systems that monitor and control industrial processes Camera Viewpoint Planning

Software that determines the field of vision required by a camera to provide information to an operator of a robotic device

Table 3 - Mechatronics Technologies Applicable to Resources Industry Automation


30

OTHER CHARACTERISTICS OF RESOURCES INDUSTRY AUTOMATION SYSTEMS

Perhaps the two most distinguishing characteristics of resources industry automation systems are the

extensive application of field robotics in a technically challenging environment, and the critical nature of a

centralized, often remotely located operations centre that is necessary for whole of operation optimisation.

FIELD ROBOTICS

There is a long history of automation technology being successfully developed for use in clean, stable and

predictable industrial processes such as on a manufacturing line. Field robotics is distinguished from more

traditional automation by its focus on large-scale outdoor autonomous systems in applications that are

characterised by relatively unstructured, difficult and often hazardous environments. It draws together the

most advanced research areas in robotics, including navigation and control, sensing and data fusion, safety and

reliability and planning and logistics. It aims to develop autonomous robotic systems capable of operating in

highly challenging applications including mining, construction, cargo handling, agriculture, subsea and

aerospace systems.

Central to most field robotics applications is the concept of an autonomous vehicle. It is this component of a

field robotics system that presents the greatest operational challenges. Terrestrial, marine and aeronautical

applications require the machines to operate in rain, snow, fog, humidity, dust, day and night. The sensors

used for automation must be functional under these conditions, and robust to tolerate the water, dirt, mud,

vibration and shock they can encounter as the machine engages the environment.

In many terrestrial applications the terrain is uneven or otherwise treacherous, and can be characterized by

hazards such as potholes, ruts, thin branches and rocks that are occluded by features such as tall grass or steep

slopes that are difficult to detect for such equipment, but necessary for ensuring safe passage. The operational

environment may be uncontrolled in the sense that people, other biological entities and other machines can

enter the environment. Furthermore, rigging the environment with infrastructure to assist vehicle automation

may be challenging or prohibitively expensive. For example an underground coal mine will require new

infrastructure continually, as material is progressively removed and the coal-face advances.

The ability to detect humans is the most important capability for the safe operation of autonomous vehicles.13

It is generally accepted that for safety reasons humans should be prohibited from entering an environment

where autonomous vehicles are operating. This is typically ensured by electronic lockouts or physical barriers

that ensure automatic shutdown of automated systems before humans approach them for inspection,

maintenance, or to perform tasks in their vicinity. In mining, particularly underground mining, this can prove

problematic. For example, lockout measures have limited the use of mobile mechanised equipment to the

production phase of block caving operations.14

In the petroleum industry, operating remote and automated equipment in very deep water presents a range of

problems associated with extreme pressures, temperatures and visibility. In aeronautical applications air-

safety precautions particularly in areas of high air-traffic frequency or ground populations are paramount.

However, it is the reduced risk of obstacle collision in many marine and aeronautical applications combined

with the significant OH&S and cost savings that occur from removing humans from devices in such

13

Steiner, J., JPL Robotics Technology Applicable to Agriculture, NASA Jet Propulsion Laboratory and USDA Agriculture Research Service 14

Noort, D. and McCarthy, P. (2009), Automated Underground Mining, International Mining January Edition


31

environments that have seen a higher level of adoption to date of field robotics in these applications for the

resources industries (subsea ROVs and airborne survey ROVs) than in terrestrial applications.

The range of tasks performed by a single field robotics device may be quite large, making full automation a

difficult task at best. Also it is not enough for automation machines to merely function, they must also perform

such that they are faster, less expensive, and/or safer than the human equivalent. In light of the fact that even

so called unskilled labour is quite adept at the logic and motor skills that robotics seeks to imitate, this

competition is significant. 15

THE CENTRAL OPERATIONS CENTRE

Perhaps the most important aspect of automated mining and petroleum production systems is that they

create the opportunity to centralize the monitoring and control of all the processes that comprise the

operation to a single physical location. The ability to locate some front-line workers to a central, and

increasingly remote, Operations Centre (OC) where they can apply their knowledge to analyzing and

interpreting operational data streams from sensors attached to equipment in the field, historical and real-time

operational data from across the operation, and other third party data sets, creates a decision environment for

effective and efficient problem solving, and opportunities to optimize operations that have not previously

existed in many sectors of the resources industry.16

An OC is a major facilitator of integrated operations.

Having multi-disciplinary experts from different components of the production system sitting in the same

room can deliver significant productivity improvements, as can having experts of the same discipline, say plant

operators, from different sites sitting in the same room sharing ideas and learning from each other.17

In effect, an OC allows operators to overcome the ‘fog-of-mining’ and facilitates ‘whole-of-operations’

optimization, similar to the way that an Electronic Warfare Operations Centre overcomes the ‘fog-of-war’ in a

military context. In one particular iron ore sector ‘whole-of-operation’ automation trial, the OC has been

credited with:

Identifying bottlenecks in car dumpers in the ports;

Allowing continuous operation during an extreme weather event, by virtue of its dynamic

rescheduling software re-routing trains to part of the logistics system not disrupted by the weather

event;

A 70 percent improvement in schedule reliability over a three year period; and

A 200 percent improvement in the proactive initiatives from maintenance staff, where ‘whole-of-

operation’ visibility has allowed them to better align maintenance tasks. 18

An OC will most likely deliver the greatest benefits where a single company owns the entire operating

infrastructure, say from mine to market delivery. This explains the significant prevalence of OCs in the oil and

gas industry, and the current significant investment in whole-of-operation automation in the Pilbara iron ore

sector.

15

Stentz, A. (2001), Robotic Technologies for Outdoor Industrial Vehicles, Robotics Institute, Carnegie Mellon University, Pittsburgh 16

Crozier, R. (2012), Humans key to automated mines, 17

Dyson, N. (2012), ‘Robominer’, Mining Monthly, April Edition 18

Dyson, N. (2012), ‘Robominer’, Mining Monthly, April Edition


32

The challenges associated with implementing an OC are primarily ones of orgnanisational structure and

culture, rather than technology. Because an OC is a very different working environment to a typical mine, or

even a typical on-site control room, significant change in the culture of the organization, team structures and

work patterns and internal communication is required. This issue is discussed in detail in a later section of this

report. Figure 5 below is an illustration of the Woodside iOps OC, designed for Woodside by Integrated Energy.

This is clearly a very different environment to a typical production platform, LNG plant or mine operation. The

Woodside iOps OC is distinctive in the industry in that it covers the full value stream (reservoir, drilling,

production and production off take), with real-time process control, tactical collaborative support and decision

making, as well as health, safety and environment functionality within the single OC.

Figure 5 - A Typical Remote Operations Centre19

THE EVOLVING CHALLENGE FOR THE RESOURCES INDUSTRY WORKFORCE

The increasing adoption of automation presents a critical challenge to the resources industry, as many of the

technologies discussed above, and the integration of those technologies is not supported by a conventional

resources industry workforce. Additionally, the skills, work patterns, leadership models and culture that are

necessary to support an integrated operations approach to optimizing the benefits from automation are

typically not present in a resources company, particularly in the mining sector. This is illustrated conceptually

in Figure 6 below.

19

Figure used with the permission of Integrated Energy


33

Figure 6 - The Key Challenge Presented by Automation

As a result, over time, vocational education and training, higher education and internal professional

development programs will need to evolve to facilitate the required change in workforce skills and culture. In

the interim, it is likely that resources companies will complement their existing workforce by sourcing skills

from other industries. This is discussed in detail in a later section of this report.

KEY CENTRES OF EXCELLENCE IN RESOURCES INDUSTRY AUTOMATION AND ROBOTICS

The application of field robotics to develop highly automated outdoor processes is at the cutting edge of the

science of robotics. This section of the report briefly summarises robotics research programs in Australia,

together with some of the World’s leading robotics research centres. This is relevant to the subject of this

report because many of these research centres are involved in robotics undergraduate and graduate education

programs, and in some case delivering proprietary training to specific operations.

Main Implication for the Resources IndustryWorkforce

Sensor Technologies

Database and DataFusion Technologies

Logic Software

Visualisation &Simulation Technologies

NetworkingTechnologies

MechatronicsTechnologies

GPS, Precision GPS, mmRadar, Scanning Laser Range Finder,Infrared Spectrometer, StrainGauges, Resolver and Encoders,LVDT Sensors, Intertial Sensors,RFID etc

PLCs. Embedded PCs, multi-Core computers etc

2D & 3D media, virtual reality etc

Predictive software that determineslikely whole-of-operations outcomesfor a set of actions

Internet, satellite, microwave,fibre optics, communicationsProtocols etc

Electric Drive Systems, Hydraulic Drive Systems, Robotic Task Allocation, SCADA Control etc

Field robotics

Storage and interrogation of vastQuantities of data

Code that facilitates the integrationand interrogation of hetrogenousdata sets

CollaborationTechnologies

Video, audio and data connectivitybetween mobile devices and devicesIn fixed locations

Operations CentreSystems that facilitate the monitoringand control of the entire operationfrom a single central location

Many of these technologies,and the integration of these

technologies is not supportedby a conventional resources

industry workforce ororganisational culture


34

AUSTRALIAN ROBOTICS RESEARCH

In the past 15 years, Australia has come to lead the world in the development and application of robotics in

large-scale outdoor field applications. Robotics and autonomous systems will be one of the most important

and transformational technologies in the future of Australia. In the future, one of the next big applications

from robotics will be in the stewardship of the natural environment, both in the marine domain and for

terrestrial ecosystems. Australia has the skills and opportunity to lead the way in these endeavours. There are

also many opportunities in remote healthcare, infrastructure maintenance and management of disasters

including bush fires.20

The key robotics research centres in Australia are the Australian Centre for Field Robotics (which includes the

Rio Tinto Centre for Mine Automation), the Cooperative Research Centre for Mining’s Automation Program

and the CSIRO’s Transforming the Future Mine Program.

THE AUSTRALIAN CENTRE FOR FIELD ROBOTICS AND THE RIO TINTO CENTRE FOR MINE

AUTOMATION

The Australian Centre for Field Robotics (ACFR) is based at the School of Aerospace, Mechanical and

Mechatronic Engineering at the University of Sydney. Its research focuses on the development, application and

dissemination of autonomous and intelligent robotics for operations in the outdoor environment.

The ACFR was established in the early 1990s with ten staff. In 1999 it became an Australian Research Council

(ARC) Key Centre, and in 2003, an ARC Centre of Excellence. Today, the ACFR has over 100 academic, research

and engineering staff members. It is recognised as being one of the world’s largest robotics research groups.

Researchers at the ACFR have been instrumental in the development of a number of the core technologies

that form the foundation of field robotics today, including the SLAM algorithms which have become arguably

the most important single piece of international robotics research in the past 15 years. This project was critical

to establishing the international reputation of the ACFR.21

The AFCR has substantial experimental facilities including three laboratories and a field test site, a range of

experimental and production vehicles, industry-quality mechanical and electrical design and fabrication

facilities, and the latest embedded computing, sensing and control technologies. It has established a number

of leading research centres that are funded by the Australian Research Council (ARC), mining, security and

defense and environmental agencies.

The AFCR undertakes fundamental and applied research in field robotics and intelligent systems that

encompass the development of new theories and methods, and the transfer of these to industrial, social and

environmental applications. The research program at the AFCR focuses on enabling field robotics in the four

areas summarised in Table 4 below.

20

Durrant-Whyte, H. (2010), The Robots are Coming: The Robotics Revolution in Australian Industry, The Warren Centre for Advanced Engineering 21

Durrant-Whyte, H. (2010), The Robots are Coming: The Robotics Revolution in Australian Industry, The Warren Centre for Advanced Engineering


35

Sensors, Fusion and Perception

Actuators, Control and Decision

Modeling, Learning and Adaptation

Architecture, Systems and Cooperation

Sensing

Representations of information

Modeling and management of uncertainty

Data fusion

Perceptual interpretation

Of individual micro and macro machines

Of heterogeneous groups of platforms and sensors

Of contact and interaction with the environment and each other

Supervised and unsupervised learning in unstructured and dynamic environments

Multi-agent learning

Pattern recognition

Concept formation and adaptation to the environment

Design and optimization of ‘systems of systems’

Modeling and management of complexity

Large scale systems theory

Modeling of information flow, negotiation and cooperation between platforms and intelligent systems

Table 4 - Major Research Themes at the Australian Centre for Field Robotics

The AFCR also supports education programs across the university. In particular it supports post-graduate

students, and industry training programs. AFCR staff deliver various subjects for the degree of Bachelor of

Engineering in Mechatronics Engineering at the University of Sydney (this is discussed in detail in a later

section of this report).

The AFCR has a very strong industry focus. It works with industry to build and maintain links with both system

developers and end-user industries. The AFCR has four affiliated centres, including the Rio Tinto Centre for

Mine Automation (RTCMA). This centre was established in 2007 with Rio Tinto committing $21 million for an

initial five year period. The aim of the RTCMA is to develop and implement the vision of a fully autonomous,

remotely operated mine. It aims to automate surface mining as a process, especially focusing on issues of data

fusion, systems architecture and integration of platforms and information into the mining operation.

The RTCMA has a range of programs underway that cover sensing, machine learning, data fusion and systems

engineering. It is working closely with Rio Tinto on the implementation of its Mine of the Future program

(discussed in a later section of this report). The RTCMA program is structured according to three main sub-

programs:

The technology program has the objective of applying and developing existing and new technology to

the automation of current mining operations in the areas of drilling, loading, haulage and to integrate

these into a coherent mining automation system;

The research program has the objective of developing key enabling technologies for automated and

remote mining including, sensing, data fusion, machine learning, machine control and mine systems

engineering.

The training program aims to deliver new skills and trained graduates in mining automation, enabling

Rio Tinto to support and make best use of automation across its global operations.

The AFCR is discussed again in the case study section of this report.


36

CRC MINING AUTOMATION PROGRAM

The CRC Mining was established under the Australian Government’s Cooperative Research Centres (CRC)

program in 2003, with initial Federal Government funding of $27 million over seven years that is leveraged

against approximately $100 million of funding and in-kind support from university and industry partners in the

CRC Mining. In 2009, the CRC Mining received a $12 million five year extension from the Federal Government.

Table 5 below summarises the current partners in the CRC Mining.

Industry Partners University Partners Anglo American AngloGold Ashanti Barrick Gold Corporation BHP Billiton Caterpillar CSC Herrenknect Tunnelling Systems Newcrest Mining Limited Newmont Mining P&H Minepro Services Peabody Energy Sandvik Xstrata

University of Newcastle University of Queensland University of Western Australia Curtin University

Table 5 - CRC Mining Partners

The CRC Mining’s research program is organized according to the themes of:

Rock fragmentation;

Drilling processes for fugitive emissions;

Equipment and power management; and

Automation.

The automation program undertakes fundamental and applied research in the areas of:

Control strategies that enable automated machines to operate independently with other equipment;

Situational awareness capabilities;

Integration of automated machinery into mine systems; and

Workforce skills that must be enhanced to support the deployment of high-end automation

technologies

The CRC Mining has successfully commercialized a number of outcomes from its automation program through

a spin-out company, Acumine, including:

Haulcheck – a system using lasers to maintain large haul trucks on a roadway;

mm-wave radars for monitoring stopes and ore-passes in underground mining;

Proximity monitoring systems for mine operations to ensure safety22

22

Durrant-Whyte, H. (2010), The Robots are Coming: The Robotics Revolution in Australian Industry, The Warren Centre for Advanced Engineering


37

CSIRO TRANFORMING THE FUTURE MINE PROGRAM

Under the CSIRO’s Minerals Down Under Flagship program, the CSIRO operates a research subprogram known

as Transforming the Future Mine Program. This subprogram is comprised of the following three themes:

Enhancing knowledge from drilling, which is designed to deliver to industry new and effective drilling

technologies that will significantly reduce drilling costs, increase rates of exploration, provide a

greater quantity and quality of data acquired from boreholes in exploration and improve control of

rock fragmentation in mining;

Geologically intelligent surface mining, which is designed to develop advanced automated methods

of continuous surface mining using machines equipped with novel cutting technologies, geology-

based guidance systems and new design principles for open cut mines resulting in minimized dilution,

increased recovery, increased mining rates, providing material discrimination or sorting near mining

faces and enabling real-time operational control from remote world-wide centres through advanced

knowledge of human-machine environment interactions; and

Non-entry underground mining, which will focus on developing technologies that enable non-entry

methods of underground mine development and construction that reduce OH&S risk and mining

costs and bring ore bodies on stream sooner.

The CSIRO has been particularly active in underground coal mining with projects funded by the Australian Coal

Association Research Program (ACARP) in long-wall mine automation and rapid roadway development

systems.

OTHER AUSTRALIAN ROBOTICS RESEARCH CAPABILITY

Other universities in Australia have smaller programs that contribute to Australia’s resources industry

automation scientific capability. For example:

The School of Mining Engineering at the University of New South Wales has significant capability in

simulation technology that is applied to the coal industry; and

Researchers at Curtin University undertake research in automated haul systems, and haulage road

design and maintenance for an automated environment, as well as in resources operations machine

learning, data mining, data visualization, smart sensors, evolutionary computation, computer vision

and expert systems

INTERNATIONAL ROBOTICS RESEARCH

There are a number of global centres of excellence in robotics research. Two of particular interest to resources

industry automation are the United States National Robotics Initiative and Carnegie Mellon University’s

Robotics Institute, and the National Robotics Engineering Centre


38

UNITED STATES NATIONAL ROBOTICS INITIATIVE

The United States National Robotics initiative involves the National Science Foundation, the National Institutes

of Health, NASA and the Department of Agriculture, which combined will make available up to $70 million per

annum to fund new robotics projects. The goal of the National Robotics Initiative is to accelerate the

development and use of robots in the United States that work beside, or cooperatively with people. Innovative

robotics research and applications emphasizing the realization of such co-robots acting in direct support of and

in a symbiotic relationship with human partners is supported by multiple agencies of the federal government

including the National Science Foundation (NSF), the National Aeronautics and Space Administration (NASA),

the National Institutes of Health (NIH), and the U.S. Department of Agriculture (USDA). The purpose of this

program is the development of this next generation of robotics, to advance the capability and usability of such

systems and artifacts, and to encourage existing and new communities to focus on innovative application

areas. It will address the entire life cycle from fundamental research and development to industry

manufacturing and deployment. Methods for the establishment and infusion of robotics in educational

curricula and research to gain a better understanding of the long term social, behavioral and economic

implications of co-robots across all areas of human activity are important parts of this initiative. Collaboration

between academic, industry, non-profit and other organizations is strongly encouraged to establish better

linkages between fundamental science and technology development, deployment and use.

Two classes of proposals will be considered in response to this solicitation:

1. Small projects: One or more investigators spanning 1 to 5 years. 2. Large projects: Multi-disciplinary teams spanning 1 to 5 years.

23

CARNEGIE MELLON UNIVERSITY ROBOTICS INSTITUTE AND THE NATIONAL ROBOTICS

ENGINEERING CENTRE

The Robotics Institute at Carnegie Mellon University was founded in 1979 to conduct fundamental and applied

research in robotics technologies relevant to industrial and societal tasks. With over 100 projects underway,

the Robotics Institute is the world’s largest university affiliated robotics research group. The Robotics

Institute’s facilities are spread across Carnegie Mellon’s Oakland campus, the National Robotics Engineering

Centre in Lawrenceville and the Field Robotics Centre in Hazelwood in Pittsburg, Pennsylvania.

The Robotics Institute is structured according to the following research centres:

Centre for Integrated Manufacturing Design Systems

Centre for the Foundations of Robotics

Magnetic Levitation Haptic Consortium

Medical Robots Technology Centre

National Robotics Engineering Centre

Quality of Life Technology Centre

Vision and Autonomous Systems Centre

23

http://www.nsf.gov/funding/pgm_summ.jsp?pims_id=503641&org=CISE (Accessed 18 April 2012)

http://www.nsf.gov/funding/pgm_summ.jsp?pims_id=503641&org=CISE


39

Field Robotics Centre

The National Robotics Engineering Centre (NREC) is a technology transfer organization that designs, develops

and tests robotic systems and vehicles for industrial and government clients. The NREC combines systems

engineering disciplines of requirements and trades analysis, design, simulation, integration and test with

applied research capabilities in autonomy, sensing and unmanned platform design. The NREC excels in rapid

integration and field-testing of automated systems. Several of their systems have transitioned to applications

in industry and the military.

The National Robotics Engineering Centre is currently undertaking the following two projects that are relevant

to the resources industry:

Assisted Mining, which is investigating the application of robotic sensors to the development of semi-

automated continuous mining machines and other underground mining equipment. Sensors mounted

on the mining equipment can accurately measure the machine's position, orientation and motion.

These sensors will assist operators standing at a safe distance to precisely control the machine; and

Underground Mining Operator Assist, which is focusing on automating the functions of a continuous

mining machine and roof bolting units in underground coal mining.


40

THE ADOPTION OF AUTOMATION IN THE AUSTRALIAN RESOURCES INDUSTRIES

Most arguments supporting the notion that there will be increased adoption of automation in the resources

industry, cite one or more of the following as key drivers of adoption:

Improving operations productivity through improved labour and capital utilization, speed and

accuracy and whole of operations optimization;

Increasing access to resources that could not be extracted without the use of automated, particularly

remote controlled, systems;

Reducing the current reliance on tight resources sector labour markets;

Improved OH&S that results from removing humans for inherently hazardous operating

environments;

Improved employee retention that results from a shift in the balance of job tasks profiles from

manual tasks to knowledge based tasks, a safer working environment and an increase in centrally

located roles; and/or

Reduction in externalities that result from more precise and efficient operations. 24&25

Whilst, generally speaking, these factors are positive attributes that are typically associated with automated

resources operations systems, the fact is that resources operations are highly variable in terms of strategy,

operational layout, upstream and downstream integration, OH&S issues, environmental issues and general

suitability to various degrees of automation. As such, the compelling case to invest in automated systems is

highly variable among resources industry operations, and such generalizations are not adequately compelling

in many case. These general drivers of adoption of automated systems in the resources industry are discussed

in more detail in a subsequent section of this report.

Indeed, predicting the level of future adoption of automation by various sectors of the Australian resources

industry with a reliable degree of certainty is a very difficult task. In an attempt to better illuminate the issue

this section of the report:

1. Summarises two frameworks that are widely accepted as being useful for at least explaining the

dynamics of adoption for a particular adopter and how innovations penetrate markets;

2. Examines the dynamics around adoption of field robotics based automation in two other industries

being port freight terminals and agriculture;

3. Discusses the general drivers of adoption of automation in the resources industry; and

4. Discusses the current degree of adoption and challenges to the adoption of automated systems in a

selection of sectors of the Australian resources industry.

24

Frese, A., Global Mining Solutions & Product Support Manager, Caterpillar in Business/Higher Education Roundtable (2012), IT&C, Technology, Skills –Investing in Fieldnomics of Mining Automation and Innovation Round Table, CSC 25

McGagh, J (2008), in CIM Magazine, Vol. 4, No.1


41

A FRAMEWORK FOR ASSESSING THE DYNAMICS OF INNOVATION ADOPTION

In assessing the potential rate and extent of adoption of automated systems in the various sectors of the

Australian resources industry, two well established frameworks can be used to more clearly articulate the

issues.

FACTORS THAT DETERMINE THE RATE AND EXTENT OF ADOPTION OF AN INNOVATION

There is a significant body of empirical evidence that supports the notion that the following five factors

describe 49 to 87 percent of the variance in rate and extent of adoption of any innovation in any industry:26

Relative Advantage

Relative advantage refers to the degree to which the adopter perceives the innovation as being better

than the current practice or technology, which can include doing nothing. The improvement can be

measured objectively or subjectively by the adopter according to a range of criteria including

economics, convenience, safety, prestige etc. Innovations demonstrating a strong relative advantage

are more likely to be adopted.

Compatibility

Compatibility refers to the degree to which an innovation is perceived as being consistent with the

existing values, experiences, needs, processes and business systems of the adopter. Innovations that

are compatible are more readily adopted.

Complexity

Complexity refers to the degree to which an innovation is perceived as being difficult to understand

and use. The more simple the target adopter perceives the innovation is to understand and use, the

more likely the innovation will be adopted.

Trialibility

Trialibility refers to the degree to which an innovation may be experimented with on a limited basis to

reduce the risk that in practice it does not deliver on the adopter’s expectations of relative advantage

and compatibility. Innovations that can be trialed on a limited basis before an adoption decision is

made are more likely to be adopted.

Observability

Observability refers to the degree to which the results of an innovation are visible or measurable and

the degree to which the benefits can be directly linked to the adoption of the innovation. The easily

and rapidly potential adopters can observe the results of using the innovation the more likely they are

to adopt.

Other factors such as the nature of the adoption decision (individual or group decision) and the extent of the

effort to promote the innovation to target adopters also impact on the rate and extent of adoption of an

innovation, but have much less impact than the factors discussed above.

26

Rogers, E. (2003). Diffusion of Innovations, 5th

Ed., Free Press, New York


42

THE MARKET FOR NEW INNOVATIONS

The market for any specific innovation is comprised of five segments of adopters that demonstrate very

different innovation adoption behaviours with respect to that specific innovation. If the population of the

market for a specific innovation was normally distributed, these segments may be distributed similarly to the

distribution shown in Figure 7 below.

Figure 7 – Segmentation of the Market for New Innovations

Innovators are the first adopters of a technology and are prepared to take considerable risk in working with a

new innovation in an attempt to get it working for its operations, when the rest of the industry would consider

the innovation too premature. Early adopters are typically those firms that are considered innovative. They will

take some technology risk, but only on the basis of deep technical and commercial due diligence, and expect

returns from their investment in risky technology to be commensurate with the risk they are taking. The early

majority market segment is comprised of more prudent and pragmatic companies that consider innovation in

the context of seeking incremental, measurable and predictable improvement in business performance. They

are pushed to the front of the majority market by demands for maintaining a certain level of productivity. Late

majority adopters tend to only adopt the innovation when there is enough evidence in their industry that the

innovation performs adequately, and they are forced to adopt to remain competitive. Laggards may never

adopt the innovation and often, over time, become uncompetitive.27

As innovations penetrate a market they move through these different segments of adopter behaviours. Most

innovations that enter a market and achieve some penetration fail to transfer from early adopters to the early

majority, as this transition represents the biggest challenge.28

27

Rogers, E. (2003), Diffusion of Innovations, 5th

Ed., Free Press, New York 28

Moore, G. (2004), Crossing the Chasm: Marketing and Selling Technology Products to Mainstream Customers, 2

nd Ed, Capstone Publishing, West Sussex

Innovators

(2.5%)

Early Adopters

(13.5%)

Early Majority

(34%)

Late Majority

(34%)

Laggards

(16%)

Early Market (16%) Majority Market (68%) Late Adopters (16%)


43

ADOPTION OF AUTOMATION IN OTHER INDUSTRIES

Robotics and ICT have and continue to dramatically change the industrial sector, as mechanical power did

during the industrial revolution.29

It is generally recognised that the automation of manufacturing processes

through the application of robotics commenced in 1961 when General Motors installed a 1.8 tonne robotic

arm known as Unimate to its production process. It is the automotive manufacturing industries in the United

States, Asia and Europe that have driven the adoption of robotics in manufacturing lines. Indeed, the sector

dominated the market for manufacturing robots right up to the mid 1990s, when 90 percent of robots in the

North American market were purchased by automotive manufacturers.30

However, by the beginning of this century, while approximately 90 percent of all robots in use were deployed

in manufacturing factories, only 50 percent of new robots were being acquired by automotive manufacturers,

with robots increasingly being deployed in a wide range of environments where they can replace humans for

tasks that are repetitive, dangerous or difficult, such as many tasks undertaken in warehouses, laboratories,

energy plants and hospitals.31

It is estimated that the number of robots deployed in North American industry has grown from 140,000 in

2004 to 216,000 today, with North American customers purchasing a total of 4,605 robotic devices worth

US$300 million in the first quarter of 2012.32

It is important to note that despite the proliferation of robotics in manufacturing industries, full automation is

very rare. The automotive manufacturing industry, for example, does not currently consider full automation to

be cost effective and has found that partial automation achieves 90 percent of the benefits of full

automation.33

For most manufacturing applications a number of factors work in favour of automation, including the fact that

in these applications robotic equipment:

Is commonly deployed in indoor, clean and structured environments;

Is often stationary and not required to be mobile, or where mobile equipment is required it tends to

only navigate over known terrain, often according to a predetermined pathway that does not vary;

Is often only required to handle materials of known types or from a limited set of classes;

Is likely to be required to engage in repetitious tasks that are limited in scope and complexity,

reducing the need for sophisticated planning and offering enhanced opportunity to learn from

mistakes and fine-tune performance; and

Can often deliver significant benefits through partial automation of the process as many

manufacturing processes incorporate a large number of simple, repetitive tasks that can be easily

automated, and significantly fewer tasks that have variability and require sophisticated reasoning that

29


Doe, C., Robots in Manufacturing, CSC 105-02 31

Doe, C., Robots in Manufacturing, CSC 105-02 32

Robotic Industries Association (2012), Robotics Industry Off to a Great Start in 2012 33



44

can be performed by human operators and for which automation would provide only incremental

benefits, if any at all.34

For less structured outdoor industrial processes such as freight handling, agriculture and resources industry

operations, the introduction and adoption of automation and robotics has been much slower due to the level

of complexity associated with the nature of tasks robots are required to perform, and the uncertain nature of

the environment in which they are required to perform them.35

This section of the report presents two case studies that demonstrate some of the challenges with deploying

automation to outdoor operating contexts, and indicate that despite the complexities in the environments in

which automated systems are deployed, some initial market penetration is occurring in specific applications.

CASE STUDY: AUTOMATED PORT CONTAINER TERMINALS

As a field operating environment where automation and remote control technology can be applied, port

container terminals represent an interesting ‘mid-point’ in application between a manufacturing factory

environment and a typical resources operating environment. With respect to the potential application of

automation, a container terminal environment is similar to a manufacturing environment in that it is relatively

uniform and organized, but bears similarity to a typical resources operation in that it involves large mobile field

equipment, moving heavy loads in an outdoor environment.

THE FIRST ATTEMPT AT CONTAINER TERMINAL AUTOMATION

In the early 1990s, a robotics scientist, Professor Hugh

Durrant-Whyte and a former military captain, David Avery,

were hired by a logistics consulting firm that was working on a

new container terminal planned for the Thames-Medway

estuary in the United Kingdom to investigate the potential to

design the new container terminal systems such that they

could take advantage of emerging automation systems.

Specifically, Hugh Durrant-Whyte and David Avery were

engaged to assist with the identification of suitable sensor

technologies for a planned automated rail-mounted gantry

crane.

As planning for the new terminal gained momentum, the opportunity arose to experiment with the

automation of a large, flatbed vehicle capable of moving containers between the quay and gantry cranes. The

group was successful in gaining financial support from United Kingdom Government and European Economic

Community grant programs, as well as from Thames Port and Terbergy BV, a container terminal equipment

manufacturer. The development of a demonstration proto-type was commissioned in 1993. While the

34


Ibanez-Guzman (1995), ‘Comparison between industrial robotic manipulators, agricultural and construction plant and equipment, Automation and Robotics in Construction,


45

resulting equipment, the FRIAT 80 System (see picture above), was never commercialized, its development

gave rise to many technological advances in field robotics in the areas of vehicle modeling, systems integrity,

perception radar and real-time vehicle control that became the basis of subsequent endeavours in port

container terminal automation and field automation in general.

THE AUSTRALIAN WATERFRONT DISPUTE

In the early 1990s the Australian stevedoring company, Patrick, had commenced an initiative to improve

productivity at its Australian port operations. In 1996, the conservative government led by John Howard was

elected and one of its policy platforms was to improve productivity on the Australian waterfront. In 1998 the

Australian Productivity Commission published an international benchmarking study of the Australian

waterfront that concluded that productivity at Australian port container terminals, as measured by Net Crane

Rates, was substantially below that of comparable international port container terminals.36

This study

supported the newly elected Government’s pursuit of its policy to improve productivity on the Australian

waterfront, as well as Patrick’s objective of improving the efficiency and productivity of its operations.

Collectively, these events culminated in the 1998 Australian waterfront dispute between Patrick and the

Maritime Union of Australia (MUA). In addition to the two main protagonists, this dispute involved the new

Conservative Federal Government, National Farmers Federation, Australian Council of Trade Unions, officials

from other unions and opposition Federal parliamentarians and became, arguably, one of the most important

industrial disputes in Australia’s history.37

A SOLUTION IN AUTOMATION

While Patrick’s endeavours to improve productivity at its container terminals focused primarily on this

controversial industrial dispute, its program also included the development of new container terminal

technology designed to improve the overall efficiency of its operations.

The research group associated with the Thames-Medway Estuary automated terminal project had since

transferred to Sydney University’s Australian Centre for Field Robotics (see previous section of this report).

Impressed by the work on the high-speed crane and the FRIAT 80 System project at the Thames-Medway

Estuary Terminal, Patrick tasked the Sydney University group with developing an automated straddle carrier, a

vehicle used for stacking containers in a yard and moving them to and from the cranes to the yard and trucks

and the yard.

In conjunction with Sydney University’s Australian Centre for Field Robotics, Patrick was successful in securing

an Australian Research Council (ARC) Linkage Grant to develop this technology. Work commenced on the

project at a covert site at St Mary’s, western Sydney in late 1997.

After three years of R&D the first demonstration of the automated straddle carrier, known as AutoStrad™, was

undertaken by way of a limited trial in a small area of the Port Botany container terminal yard in Sydney. The

Board of Patrick was sufficiently impressed with the technology that it formed a new company, Patrick

Technology and Systems, and employed the lead engineers from the Sydney University team to further

develop the technology to a deployable system.

36

Productivity Commission (1998), International Benchmarking of the Australian Waterfront, Productivity Commission, Melbourne 37

Griffin, G. and Svensen, S. (1998), Industrial Relations Implications of the Australian Waterside Dispute: Working Paper No. 62, National Key Centre for Industrial Relations, Monash University, Melbourne


46

In late 2000, Patrick acquired a small terminal at the

Port of Brisbane from CSX World Terminals to use as an

operational trial site for the AutoStrad system. The trial

system involved the deployment of five AutoStrad units

and allowed Patrick to further develop the technology

in an operational environment and at a manageable

scale. Identifying technology and systems issues

associated with operational scale-up of the system were

not insignificant and this site was critical in facilitating a

low risk escalation of automated operations. In effect

this small site allowed Patrick to test and trial not only

the technology but the systems and processes, including

safety and human resources processes. The terminal

was a microcosm of the larger facility that was

eventually built alongside it. To place these challenges

in context, the first trials involving an actual ship loading

and de-loading operation didn’t occur at the site until

2002.

Full operational scale-up of the AutoStrad system did

not commence until 2005, when a system based on 18

AutoStrad units was deployed at Patrick’s Fisherman

Islands terminal at the Port of Brisbane. By 2009, the

Fisherman Islands terminal was operating an automated system based on 27 AutoStrad units on a 39 hectare

container yard site that services Berths 8, 9 and 10 along a 900 metre long quay line. This facility is operated by

160 stevedoring staff and has a capacity of more than 1.2 million Twenty-foot Equivalent Units (TEUs) per

annum.

The AutoStrad units (see above picture) weigh approximately 60 tonnes and travel at speeds of up to 27

kilometres an hour. Positioning and navigation is achieved by a combination of precision GPS and millimeter

wave (mm-wave) radar. They are guided around the terminal yard via a complex traffic management system

that uses virtual nodes, comprised of surveyed way points located within the yard compound. These nodes are

not hard-wired, providing a considerable degree of flexibility in yard layout and operations38

, and very

importantly, the ability to deploy the system in a brownfields container terminal with limited switching costs.

The automated Fisherman Islands container terminal has won a range of awards in various categories including

the coveted Lloyds List Industry award for “best terminal” as voted by the shipping company users of the

Australian waterfront in 2010. Port container terminals typically have three main operational key performance

indicators – occupational health and safety, productivity and freight damage minimization. The AutoStrad

system at the Fisherman Islands impacts positively and significantly on each of these key performance

indicators:

38

Port of Brisbane (2012), ‘Patrick’s Terminal: World First’, (http://www.portbris.com.au/NewsMedia/newsid537/2/Patricks-Terminal-World-First) Accessed 4 August 2012

http://www.portbris.com.au/NewsMedia/newsid537/2/Patricks-Terminal-World-First


47

Occupational Health and Safety

As with all potentially hazardous operating environments occupational health and safety (OH&S) is of

paramount importance to container terminal operations, and this is the area in which the automated

system at Fisherman Islands has had the most significant impact. Conventional straddle carriers are

awkward machines to operate, which may place ergonomic strains on operators. The simple fact that

the straddle carrier operator role is made redundant by the AutoStrad system, removes this OH&S

risk. Consistent with best practice under the standard OH&S hierarchy of risk control the risk has been

engineered out. Furthermore, the AutoStrad system removes people from 80 percent of the

operating area of the container terminal, with staff only present at the quay line, and to a very limited

extent, the truck exchange area.

The OH&S impact of automation at the Fisherman Islands Terminal is self evident. In 2002-03, prior to

automation, the Patrick’s Fisherman Islands container terminal reported a Loss Time Frequency Rate

of 177.6. In 2010-11 the Lost Time Frequency Rate at the facility was 4.2. This is a direct result of the

automated operating environment, an improved workforce culture and Patrick’s focus on health and

safety. For example, 2004-05 was the last year that the facility operated under conventional

stevedoring systems. In that year the operation experienced 40 lost time injuries and paid a worker’s

compensation insurance premium of approximately $1.0 million. By comparison, in 2010-11, the

operation experienced two lost time injuries, both of which were incurred from shipboard duties and

the workers compensation premium was $208,000.

Productivity

Minimising the time a ship is required to remain in port to unload and re-load cargo is critical to the

productivity and profitability of ports, shipping lines and stevedoring companies, as are the costs

associated with turning ships around quickly. The productivity of a port’s stevedoring operations is a

critical determinant of this key metric. The automated system at Fisherman Islands improves the

regularity and predictability of the service in line with the shipping line’s requirements. The

automated system has also seen crane movements per hour on its late generation cranes significantly

exceed 25, which was the benchmark set by the Federal Government in the wake of the 1998

waterfront dispute. It has also facilitated an increase in the number of cranes from three to five and a

reduction in the number of staff required to operate the entire facility by a factor of approximately 50

percent. The redundancy of the straddle carrier operator role has obviously contributed to the

reduction in staff numbers. However, the automated environment has increased the labour

productivity of other tasks as well. For example, whereas a typical crane gang is comprised of

anything up to 13 staff in a conventional truck and trailer operation, the crane gangs at the Fisherman

Islands facility have four staff. This is understood to be the lowest crane manning scale in the world.

The automated system has resulted in other efficiencies. For example, the Fisherman Islands terminal

has an electricity cost of approximately $130,000 per month. Because the AutoStrad units, unlike

human operated straddle carriers, do not require visual perception, and 80 percent of the facility is

void of people, a differential lighting system can be deployed across the 39 hectare site. This has

resulted in a significant reduction in electricity usage that has saved the facility $100,000 over the

past 18 months. Similarly, manually operated terminals require road-lines to be painted to guide

straddle carrier operators safely and effectively around the yard. The maintenance of these lines

would typically cost a yard the size of the Patrick Fisherman Islands terminal around $70,000 per

annum. The need for lines is largely eliminated in an automated environment. Similar savings exist in

maintenance, pavement longevity and asset depreciation.


48

Freight Damage Minimisation

Sea containers and the cargo they contain are damageable. Moving containers containing cargo on

and off ships, around a yard and on and off trucks, creates the risk that human error will lead to

damaged containers that will slow the operation as the cargo needs to be transferred to a new

container to ensure that the load can be securely and safely transported, or damage to the cargo

itself. The AutoStrads move and stack containers from the quay line into holding yards and onto

vehicles and back to quay cranes with an accuracy of better than 20mm. As a consequence, damage

in the automated environment has been significantly reduced.

As with most field automation systems, implementation of the AutoStrad system required changes to

operating systems. For example, because OH&S policy prevents people being present in areas where the

AutoStrad units are operating, gantry cranes must move containers to and from the yard via the rear legs of

the crane, which can add 40 to 50 seconds of time per lift. While the lost time is regained by a system that is

more efficient overall, it still required a significant change to the conventional operating procedures.

Furthermore, like most field automation systems, the AutoStrad units are not fully automated. The AutoStrad

units still require human intervention during the truck loading process. However, this is achieved efficiently by

a remote operator who can intervene in the automated process via a hand-held remote control system, known

as a tele-op operator. The interface environment between the AutoStrad and the truck loading process is

illustrated in the figure below, with the tele-op operators standing outside of the truck-loading bays. Most of

the tele-op operators are re-trained former straddle carrier operators.

Even though there were changes to operational processes, the requirements for new skills development were

relatively limited. Retraining of straddle carrier drivers for the tele-op operating role requires approximately


49

two days of dedicated training. Crane drivers require a similar amount of training to learn how to interface

with an automated straddle carrier.

A license to manufacture and distribute the AutoStrad units was sold by Patrick to Cargotec, an international

straddle carrier Original Equipment Manufacturer (OEM). Cargotec also has a maintenance contract with the

Fisherman Islands terminal. Maintenance of the straddle carriers is performed on site, requiring one Full Time

Equivalent (FTE) per shift.

The automated system has resulted in the creation of two new positions at Patrick’s Fisherman Islands

terminal. A mechatronics engineer is now a permanent member of staff and deals with more complex

technical issues associated with the automation system. A production manger role has also been created to

oversee the entire operation, to identify and address exceptions in the system and to optimize the operation.

This role has been filled by people with well developed IT and logistics skills, many of whom have come from a

military background.

The implementation of automation at Patrick’s Fisherman Islands terminal has also resulted in significant

cultural change. The Patrick management team at Fisherman Islands was deliberate in ensuring that staff were

a major driver of the change process. The award winning buildings and staff facilities at Fisherman Islands are

of a very high standard, with the staff having considerable input to the design. Crib facilities are spacious and

well appointed, and the facility is ‘uncommonly’ clean compared to conventional container terminals. This

combined with the removal of repetitious job of straddle driving creates a modern feel to the terminal which is

at odds with the traditional images of the waterfront. Management have consciously worked to promote the

facility as technically sophisticated, and staffed by a workforce of skilled and committed operators.

Indeed, there is significant evidence of workforce pride in the operations. For example, when the facility was

commissioned, 160 staff were invited to an open day for family and friends. Over 700 people attended this

event. A recent employee engagement survey conducted by Patrick also revealed that the Fisherman Islands

workforce were significantly happier and more satisfied with their environment than those at other Patrick

terminals.


50

ADOPTION OF AUTOMATION BY THE GLOBAL CONTAINER TERMINAL INDUSTRY

While there are still only a handful of automated container terminals around the world such as Fisherman

Islands, London Gateway, Port of Hamburg and parts of Rotterdam Port, there is clear evidence of an

increasing trend toward automation in the stevedoring industry.

Very recently, Patrick announced a capital investment plan to comprehensively redevelop and expand its

container terminal at Port Botany, Sydney by 2014. This A$348 million investment will include the introduction

of state-of-the art terminal handling technology, including installation of the AutoStrad system and eventually,

auto-stacking cranes. Patrick is expecting the following benefits from this project:

Increased labour efficiency, with an estimated 270 positions at Port Botany being made redundant by

the completion of the project when operations switch to the automated system;

A significant reduction in Frequency of Lost Time to Injuries (FLTIs) as a result of the improved OH&S

environment delivered by using an automated system; and

Increased flexibility to move to higher density modes of operation if required. 39

Collectively, these initiatives are expected to substantially improve crane efficiency rates, berth intensity and

berthing window performance.40

39

Asciano Limited (2012), ‘Port Botany Expansion and Upgrade’, ASX Release18 July


51

A SIGNFICANT CONTRIBUTION TO RESOURCES INDUSTRY AUTOMATION

A spin-off from the work with Patrick was the establishment of another new company, NavTech Engineering,

which commercialised the mm-wave radar technology used for the navigation system. This company has gone

on to become a major force in this niche area, building and supplying radar technology for container terminals,

security, debris monitoring on airport runways, traffic monitoring and many other applications, including

mining systems automation.

CASE STUDY: AUTOMATION AND AGRICULTURE

Agriculture remains largely a labour intensive industry. This is becoming increasingly problematic for

agricultural industries in developed regions such as Australia, United States, Canada and parts of Europe where

labour costs, and expectations with respect to OH&S standards are relatively high. This, in turn, has driven

increasing interest in the application of field robotics and automated systems to a range of agricultural

processes.41

The pressure to improve productivity in the agricultural industry through automation is compounded by the

migration of farmers into city dwellings and the lack of interest in young people to work in field-related

occupations.42

Additionally, new policies relating to traceability, food safety and environmental and social

impacts of agriculture, that are being introduced in some markets such as the European Union, will drive the

increased application of ICT and robotics as solutions to enhancing the surveillance and optimization of crops

and livestock from raw materials to market. 43

While the level of robotic precision required for most agricultural tasks is two to three orders of magnitude

less than that required in many manufacturing applications, automation in agricultural settings presents

considerable challenges. Unlike a container terminal (see previous case study) an agricultural operation is

typically characterized by relatively unpredictable and rugged terrain where equipment is in constant

interaction with the elements. Operational patterns are also less consistent in agricultural operations.

Additionally, agricultural systems interact with biological objects, which demonstrate significant structural and

behavioral variability that can prove very challenging for robotic systems, particularly with respect to livestock.

Table 6 below summarises areas in which automation is being applied in the agricultural industry. 44&45

40

Asciano Limited (2012), ‘Port Botany Expansion and Upgrade’, ASX Release18 July 41

Belforte, G, Gay, P. and Aimonino, D. (2006), Robotics for Improving Quality, Safety and Productivity in Intensive Agriculture: Challenges and Opportunities, Universita, degli Studi, di Torino, Italy 42

Ibanez-Guzman (1995), ‘Comparison between industrial robotic manipulators, agricultural and construction plant and equipment, Automation and Robotics in Construction, 43

Christensen, S. (2005), ICT and Robotics in Agriculture and the Related Industries: A European Approach, The European Foresight Monitoring Network 44

Christensen, S. (2005), ICT and Robotics in Agriculture and the Related Industries: A European Approach, The European Foresight Monitoring Network 45

Steiner, J., JPL Robotics Technology Applicable to Agriculture, NASA Jet Propulsion Laboratory and USDA Agriculture Research Service


52

Application Description

Product quality sensing and documentation

ICT systems that assist with product management and tracking from raw material inputs, through production, to delivery to market. This facilitates optimization of inputs, processes and logistics assuring product quality and food safety.

Information, communication and management systems

Distributed internet technologies that facilitate the integration of short range wireless networks based on RFID or MEMS technology, providing ICT networks across what are often expansive operations.

Monitoring the agricultural environment

Systems that identify the most important factors effecting the environment (greenhouse gases, dust, pesticides, climate) as well as finding and developing measures that can be taken to eliminate or reduce this negative impact.

Automated agricultural machinery Autonomous robotic equipment that will reduce the environmental impact, increase precision and efficiency and allow care and management of crops in new ways. Need to address the complex, dynamic and semi-natural environment encountered in agriculture.

Precision livestock farming Integration of genetic, nutritional and phenotype knowledge into ICT systems to survey individual animals or groups and use this information to support management decisions designed to optimize production or breeding goals. Also includes the use of new technologies for feed, milking, reproduction control and health surveillance. This also includes the application of robotic and remotely controlled systems for feeding, weighing, animal handling and milking.

Precision crop farming Optimisation of inputs and harvesting to maximize yield and profitability and reduce wastage and environmental externalities.

Table 6- Application of Automation in the Agricultural Industry

The adoption of automation in Australian agricultural industries has been mixed. In cropping enterprises,

seeders and headers that are partially automated through the application of precision GPS guided steering

systems are relatively commonplace. Relatively high rates of adoption of this technology can be attributed to a

number of factors, including:

Demonstrable short-term commercial benefits in the form of increased yield that can be attributed to

optimal seeding and harvesting that results from the technology;

An increase in the number of agricultural enterprises in Australian weighting their enterprise toward

cropping. This is the result of high grain prices during the mid 2000s and a desire by farmers to move

away from more labour intensive livestock enterprises, particularly with respect to younger farmers

who tend to have higher levels of education and a greater degree of competency with information

and communications technologies; and

The fact that partial automation of such machinery represents are relatively minor incremental

additional capital cost, and the equipment can still be used in a manual mode.

However, in other areas of Australian agriculture, particularly the livestock industry, the adoption of

automation has been patchy. While in sectors such as diary, there has been widespread adoption of partial

automation in parts of the value chain, there are multiple examples where industry efforts to drive adoption of

automation have experienced limited success to date. Individual RFID tags have been compulsory for all

Australian cattle producers and sheep industry bodies have been encouraging sheep producers to adopt RFID

tags for some time. This technology allows producers to implement very sophisticated livestock enterprise

information and management systems, integrating the tags with:


53

Wireless networks;

Databases that contain individual animal genetic, phenotype and nutrition data, information on

grazing patterns, product quality etc;

Automated grazing systems that use remote sensing to identify pasture condition and remotely open

and shut paddock gates to effect optimal grazing; and

Automated animal handling systems comprised of components such as automatic weighing and

drafting equipment.

However, very few cattle producers use the tags for anything other than simply identifying the enterprise that

owns the animal and the adoption of electronic tags for sheep has not been widespread. There are a number

of possible reasons for this, including:

In many areas of rural Australia, return on investment on land has significantly exceeded return on

investment on agricultural enterprise. This is particularly the case where an enterprise has a strong

weighting toward livestock. Using some Western Australian data as an example46,

an analysis suggests

that in 2004, in terms of average return on capital, the top 33 percent of producers earned 5.2

percent, the middle 33 percent earned 1.3 percent and the bottom 33 percent earned -3.5 percent.

Most certainly, good seasons combined with strong commodity prices can see return on capital

double from these averages. However the returns from the enterprise pale in significance to increases

in land value over the last 10 years in many regions. Whereas precision crop seeding and harvesting

delivers demonstrable short term evidence of ROI in the form of increased yield, the evidence of ROI

from investment in precision management of cattle and sheep is less consistent. Figure 8 below

illustrates rural property values for the period 1981 to 2005 in selected agricultural regions of

Western Australia.

Figure 8 - Western Australian Rural Land Values 1981 - 2005 (Selection Regions)

46

Johnston, T. (2006), Developments and Trends in Australian Farming Practices, Bedbrook Johnston Williams, Western Australia.

WA RURAL VALUES 1981 to 2005

0

500

1,000

1,500

2,000

2,500

1981

1983

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

2005

Year as at 30 June

$ P

er

Cle

are

d h

a

SCADDEN

KOJONUP

MINGENEW

WONGAN-BALLIDU


54

Forty-eight percent of Australian farmers and farm managers are aged between 45 and 65 years of

age.47

Younger farmers have a propensity to weight their enterprise more heavily toward cropping

Farming operations are typically family operated SME style businesses that have strong traditions and

limited resources for strategic planning or trials of new operating systems.

Livestock farming environments, terrain and systems are complex and highly variable, suggesting that

the introduction of automated animal management systems requires a significant amount of

customization.

There has been some traction with using RFID based systems for animal management in the sheep and cattle

breeding industry, where quantitative genetics is used by some of the more sophisticated and progressive

breeders as an input to their breeding and animal acquisition decisions.

IS AUTOMATION A COMPELLING SOLUTION FOR PORT FREIGHT TERMINALS AND

AGRICULTURE?

Comparing the case for automation in port freight container yards with that for the agricultural industry sheds

some light on the dynamics that drive adoption of automated systems in field applications. Table 7 below

summarises aspects of the adoption environment in each case based on the five factors principally responsible

for determining the extent and rate of adoption on an innovation – relative advantage, compatability,

complexity, trialibility and observability.

Factor Determining Adoption

Port Freight Terminal Automation Automation in Agriculture

Relative Advantage Automation has a significant positive impact on the key KPIs for port freight terminals – OH&S, productivity and freight damage.

The relative advantage of automation in agriculture is highly variable across enterprise types. In cropping where Precision GPS guided equipment can be used to optimize seeding, spraying, fertilizing and harvesting in order to optimize input costs and yield, there seems to be considerable relative advantage. However, in many livestock operations the relative advantage is unclear.

Compatability The implementation of the automated system did involve some structural and cultural change. There were changes to the crane ship loading and unloading procedures, some gantry crane operators were required to be retrained to remotely control the truck loading operations, and new positions of a mechatronic engineer and production manager were created and implemented into the Ports operations. The culture of the operation also had to change from a typical stevedoring environment to a cleaner, modernized factory type environment. This required some investment to effect However, the virtual node network that helps guide the Autostrad system can be deployed in any yard significantly reducing the need to invest in extensive capital or yard re-design.

Precision cropping systems are compatible because they require limited modification to industry standard equipment and represents incremental capital cost on what is a significant capital investment. It also does not require any significant changes to the general farming system and they way a farmer operates their cropping enterprise. However, applying automation technology to a livestock operation is not so compatible. It requires significant capital investment in new equipment such as automated feeders, weighing equipment and drafting equipment, automated gates, WAN infrastructure and/or data management systems. The returns are difficult to measure and need to be significant to improve the overall returns of a mixed enterprise, particularly where that mixed enterprise is located on agricultural land that is appreciating in value.

47

Australian Bureau of Statistics, (2004). ‘Paid Work: Mature Age Workers’, Australian Social Trends


55

Factor Determining Adoption

Port Freight Terminal Automation Automation in Agriculture

Complexity While a port freight terminal is an outdoor operation, it is relatively simple and involves relatively simple loading and unloading and storing operations uses a relatively standardized object (freight container).

A precision cropping system is relatively simple to understand and use as it is simply optimizing a system already used by most farmers. Livestock enterprises are far more complex operations involving a wide range of tasks that may include breeding, weaning, livestock sales, pasture management, animal health, slaughtering, milking and/or shearing. They may involve multiple species and may be integrated with a cropping enterprise. The production strategies may also be highly varied.

Trialibility The system can be tried at various scales and even in components of a larger yard and quay, serving a single berth rather than the entire stevedoring operation.

Although some elements of livestock automation such as automatic feeders and quantitative genetic systems can be trailed on a limited basis, a fully integrated livestock automation system is difficult to trial on a limited basis and typically is required to be rolled out across the enterprise, or at least major components of the enterprise for its value to be demonstrated.

Observability The benefits accrued from the implementation of the automated system are readily measurable, relatively immediate and clearly attributable to the automated system. Lost Time Injuries at the site decreased from 40 to 2 and the 2 injuries that did occur when the automated system was in place occurred outside of the operation of the automated system. Productivity was easily measureable by a resulting 50% reduction in staff and concomitant increase in crane rates, decreased energy costs and decreased site maintenance costs. There was clear evidence of reduced freight damage The automated operation received a prestigious industry award, determined by its customers.

Returns on precision cropping systems can be observed within a season in the form of reduced costs and increased outputs. However, the value of automating a livestock system can take several seasons.

Table 7 - Factors Influencing the Adoption of Automation in the Port Freight Terminal and Agricultural Industries

It would seem that adoption of automation in port freight terminals commenced with Innovators such as the

Medway Thames Estuary Group and Patrick’s initial endeavours, and that now it is moving into operations that

exhibit characteristics more akin to Early Adopter behavior. In the case of agriculture, the application of field

robotics to precision cropping seems to have entered the Early Majority segment. Whereas, in most instances

the extent of adoption of automation in livestock enterprises remains within the Innovator segment. This is

illustrated conceptually in Figure 9 below.


56

Figure 9 - Extent of Adoption of Automation in the Livestock, Cropping and Port Container Terminal Industries

In the context of adoption of automated systems, the resources industry is more similar to agriculture than

automated port freight terminals. As an operating environment, the resources industry and particularly the

minerals industry, is more similar to agriculture, in that it is a highly unstructured environment, whereas a port

freight yard is more akin to a large outdoor manufacturing plant. Furthermore, operations within the resources

industry are highly variable with respect to strategy and operations, where as the operations and strategy, and

indeed the KPIs that measure performance with respect to that strategy and operations are relatively

consistent within the industry. As such, it is reasonable to expect that the adoption of automation in the

resources industry, particularly the minerals industry will follow a pattern not dissimilar to that experienced by

the agricultural industry.

GENERAL DRIVERS OF ADOPTION OF AUTOMATION IN THE RESOURCES INDUSTRY

Automation potentially delivers a wide range of potential benefits to resources industry operations including

process transformation, increased machinery utilization, waste reduction, decreased variability in processes

and product quality, increased operational flexibility and optimized performance across the entire extraction,

processing and logistics operation.48&49

48

Al Frese, Global Mining Solutions & Product Support Manager, Caterpillar in Business/Higher Education Roundtable (2012), IT&C, Technology, Skills –Investing in Fieldnomics of Mining Automation and Innovation Round Table, CSC 49

McGagh, J (2008), in CIM Magazine, Vol. 4, No.1

Innovators

(2.5%)

Early Adopters

(13.5%)

Early Majority

(34%)

Late Majority

(34%)

Laggards

(16%)

Early Market (16%) Majority Market (68%) Late Adopters (16%)

Port Container Terminals

Cropping Systems

Livestock


57

Notwithstanding the fact that the case for adoption of automated mining systems is site specific, the general

benefits that are typically attributed to higher levels of automation primarily relate to the unique nature of

productivity in the resources industry, and a number of other benefits that can be delivered by automation

that are linked to productivity.

The resource depletion effect, relatively high cost of labour and capital effect are aspects of productivity that

are largely unique to the resources industry. Automation can have a direct impact on these aspects of

resources industry productivity, as well as potentially addressing other drivers of productivity such as whole of

operations optimization and more efficient maintenance programs. Additionally, automation delivers benefits

in several areas that are linked to productivity, namely improved resource access, reduced reliance on

conventional resources industry labour markets, reduced negative environmental externalities and improved

OH&S.

These general drivers of a decision to implement automation are summarised in Figure 10 below and

explained in detail in the following subsections.

Figure 10 - General Drivers of a Decision to Adopt Automation in the Resources Industry

IMPROVED PRODUCTIVITY

As with most industrial operations, productivity is a principal driver for the adoption of automation in the

resources industry. There is a widely held misconception that automation in the resources industry will achieve

improvements in productivity, simply by significantly reducing the size of the workforce. While automation will

most certainly render some roles in a resources operation redundant, result in some restructuring of the

workforce and potentially reduce the workforce in some sectors, it is the impact of automation on the

productivity of all factors of production (multifactor productivity) that determines whether productivity

improvements are compelling to a specific operation.

Productivity

Resource DepletionEffect

Cost of Labour Capital Effect Whole of OperationsOptimisation

Maintenance

Automation counters thenegative effect on productivity caused bya decreasing quality ofin-situ resources

Labour costs in theresources industries arehigh and automation improves the productivityof labour

Resources projects arecapital intensive and subject to long productionlead times. Automationimproves the productivityof capital

Automation providesproduces enormousamounts of operationaldata that can be used tooptimise operations

Automation may notreduce the amount ofmaintenance requiredbut may improve thepredictability of maintenance scheduling

Improved ResourceAccess

Reduced Reliance onConventional Resource Industry Labour Markets

Reduced NegativeEnvironmental Externalities

Improved OH&S

Automation facilitates accessto resources in environmentsthat cannot be safely accessedby manned equipment

The change in job functions andlocation that results fromautomation provides access toa more diverse employmentmarket

Automation facilitates moreprecise operation leading to decreased energy consumptionand smaller operational footprint

Automation removes peoplefrom dangerous operatingenvironments


58

During the period 2000-01 to 2005-06, multifactor productivity across all Australian industry increased on

average by 0.7 percent per annum, while multifactor productivity for the Australian resources industry

decreased on average by 4.1 percent per annum. During the period 2005-06 to 2010-11, significant increased

demand for raw materials from developing nations drove dramatic increases in the price of mineral and

hydrocarbon commodities. During this period, multifactor productivity across Australian industry decreased on

average by 0.7 percent, while multifactor productivity in the Australian resources industry decreased on

average by 6.2 percent per annum.50

In order to comprehend this anomaly and variation in the compelling nature of automation, one needs to

understand the unique nature of multifactor productivity in the resources industry.

RESOURCES INDUSTRY MULTIFACTOR PRODUCTIVITY

In all industries, multifactor productivity is determined by production inputs such as suitability and quality of

inputs, technology, management, skills and work practices. Productivity can be analysed according to any

single one or group of these inputs. However, the productivity of a single operation or industry is ultimately

determined by the net productivity of all inputs, measured as multifactor productivity.

The improvement in multifactor productivity that resources companies must achieve in order to remain

globally competitive has historically been relatively predictable at around 3 percent per annum, driven by a

long term downward trend in the real price of most mineral commodities and incremental process

improvement that results in the medium to long-term demise of inefficient companies.51

However, because of

a number of unique aspects of resources industry multi-factor productivity, achieving this rate of productivity

growth, particularly in the short to medium term, is somewhat challenging.

THE RESOURCE DEPLETION EFFECT

In all primary industries natural resources are inputs to the production process and as such, the productivity of

these inputs is a determinant of multifactor productivity. In agriculture the natural resource inputs are

renewable and their in-situ suitability and quality can be controlled, to a degree, through agricultural practices

such as genetics (breeding or genetic modification), fertilizers, nutrition and husbandry regimes. The nature of

mineral and hydrocarbon resources as the natural resource inputs to a resources operation is very different.

They are non-renewable and opportunities for improving their suitability and quality in-situ are very limited.

In most resources operations the higher quality ores or reservoirs are exploited first. This means that as

mineral and hydrocarbons are exploited at both an individual project level and industry level the quality and

suitability of the natural resource input decreases To put it simply, mineral and hydrocarbon resources are

becoming more difficult to find, extract and process, which means individual operations, and the industry as a

whole are extracting and processing less productive natural resources. With all other factors affecting

productivity held constant, this will result in declining multifactor productivity for the industry.

50

Australian Bureau of Statistics, Year Book 2012, Cat. 1301.0, Australian Government, Canberra 51

Upstill, G. and Hall, P. (2006), ‘Innovation in the minerals industry: Australia in a global context’, Resources Policy, (31), 137-145


59

Factors that result in the decreasing quality of natural resource inputs to a resources operation or industry are

summarised in Table 8 below.52

Minerals Operation or Industry Petroleum Operation or Industry

Decreasing ore grade Higher levels of ore impurities Difficult milling characteristics Increased portion of waste material overburden Increased depth Increased geotechnical complexity Challenging terrain or topography Complex environmental conditions Complex social conditions Greater distance to inputs Greater distance market

Decreasing reservoir pressures Increasing water depth Increasing well depth Greater distance to processing and inputs Greater distance to market Complex environmental conditions Complex social conditions

Table 8 - Factors that Contribute to Decreasing Quality of Minerals and Petroleum Resources

High commodity prices that have prevailed for the past five years have exacerbated this issue. In times of

sustained high commodity prices, resources companies are motivated to increase production volumes by

extracting and processing more from natural resources associated with existing operations. They are also

motivated to develop and exploit additional, lower quality resources that would not be economic in times of

lower commodity prices. These eventualities accelerate the depletion effect thus having a further negative

effect on multifactor productivity.

However, fortunately for the resources industry and all industries that are dependent on the raw materials

that it produces as inputs, not all other factors that affect multifactor productivity remain constant. In

particular, as a result of multi-sector investment in R&D that is motivated by a need to improve productivity,

technology improves continually. Indeed, technology is the critical, long-run factor influencing multifactor

productivity, and plays a major role in offsetting the negative effects of resource depletion.

There are numerous obvious demonstrations of

the countering effect of technology

development to resource depletion, where

advances in technology have enabled industry to

exploit resources that would have previously

been unproductive. For example, carbon-in-pulp

(CIP) processing in the gold sector, long-wall

mining in the coal sector, high pressure acid

leaching (HPAL) in the lateritic nickel sector and

subsea production and processing in the oil and

gas sector. The application of automated systems to the resources industry is merely a continuation of the

need to continually advance technology to counter the depletion effect of multifactor productivity.

52

Topp, V., Soames, L., Parham, D. And Bloch, H. (2008), Productivity in the Mining Industry: Measurement and Interpretation – Productivity Commission Staff Working Paper, Productivity Commission

‘The long run availability of mineral commodities is a

race between the cost increasing effects of depletion

and the cost decreasing effects of new technology.’

John E. Tilton University Professor Emeritus, Colorado School of Mines Profesor de la Catedra de Economia de Minerales, School of Engineering, Catholic University of Chile


60

COST OF LABOUR

On average, workers in the resources industry receive higher remuneration than those in other industries,

which is partly a function of higher average skill levels among resources industry employees, and partly a

function of the hazards and hardships of resources industry work, including the common requirement to work

in remote, isolated locations. In addition to higher wages, resources companies typically also face higher on-

costs associated with their employees including accommodation for remote workers, and FIFO transport costs.

In times of sustained higher commodity prices, resources industry worker remuneration tends to increase with

increased demand for workers, and on-costs associated with those workers also increase with increases in the

workforce. However, labour inputs account for a relatively small share (approximately 12%) of total resources

industry costs and around 23 percent of value added in the resources industry, compared to around 25% of

total costs and 52% of value added for the economy as a whole.53

That is to say, the resources industry is a

capital intensive industry. There are also major differences in cost structures within the resources industry,

with the oil and gas sector being substantially more capital intensive that the mining industry. The use of

intermediate inputs in the resources industry is also lower than the national average, mainly due to the very

low use of these inputs in oil and gas extraction.54

While the increased application of automation to the resources industry may have some impact on reducing

the industry’s reliance on a relatively expensive labour force, its principle impact will be to improve the

productivity per unit of labour input. This is achieved through a range of benefits that can be delivered by

automated systems, including:

Reduced non-operational time that results from shift changes;

Ability to immediately enter hazardous environments that would be prohibitive for manned

equipment, such as an underground mine face immediately after blasting; and

More predictable and accurate operation that results from reduced human error, leads to reduced

wear and tear, reduced need to repeat tasks, optimization of routes and task sequences, reduced

consumption of energy and other consumables and reduced risk of catastrophic failure.

Reduce the costs of labour by reducing employee numbers, as well as employee costs associated with

transporting and accommodating employees at remote mine sites and related environmental and

social impacts.55

CAPITAL EFFECT

The capital intensive nature of resources industry projects means there is an unavoidable lead time from when

capital investment decisions are made to when those assets commence production. Current measures of

multifactor productivity treat capital investment during this lead time as largely unproductive capital. In times

of sustained high commodity prices this issue is exacerbated by a number of circumstances. Firstly, in order to

increase production from existing operations and to bring new operations online there is a significant increase

53

Topp, V., Soames, L., Parham, D. And Bloch, H. (2008), Productivity in the Mining Industry: Measurement and Interpretation – Productivity Commission Staff Working Paper, Productivity Commission 54

Topp, V., Soames, L., Parham, D. And Bloch, H. (2008), Productivity in the Mining Industry: Measurement and Interpretation – Productivity Commission Staff Working Paper, Productivity Commission 55

Fisher, B. and Schnittger (2012), Autonomous and Remote Operation Technology in the Mining Industry: Benefits and Costs, BAE Economics


61

in capital investment from the industry. Secondly, this dramatic increase in capital investment exacerbates

normal lead times as government approvals processes and contractors strain under the pressure of significant

increased demand for their services. Finally, because many existing and new projects are in remote locations,

there expansion causes infrastructure bottlenecks which need to be addressed by further capital investment,

exacerbating the problem.

With 94 minerals and oil and gas projects at an advanced stage of development in Australia with an associated

capital expenditure totaling A$173 billion (average of A$1.8 billion per project)56

and many of these projects

taking several years to commence production, the capital effect on resources industry multifactor productivity

is significant.

OTHER EFFECTS ON PRODUCTIVITY DERIVED FROM AUTOMATION

The implementation of extensive automation also provides opportunities to optimize the entire operation. It

also impacts on the maintenance paradigm associated with the operation. These impacts will effect

operational productivity.

WHOLE OF OPERATION OPTIMISATION

In resources industry applications, automation needs to be considered as a total solution rather than in the

form of individual automation platforms.57

Automation and remote control systems make their greatest

contribution to productivity when they are integrated with a central operations system. In such an

environment, more informed decisions can be made on the basis of up-to-date and real time data58

The

resulting optimization improves productivity and can facilitate the efficient management of other events that

effect resources industry operation productivity such as extreme weather events.

THE MAINTENANCE PARADIGM

Maintenance requirements with automation can be reduced as a result of less wear-and-tear that is the result

of operator error, and the fact that remote monitoring of equipment and diagnostics tools can reduce the

need for physical inspection. Furthermore, the removal of an operator from a piece of equipment eliminates

maintenance associated with operator related systems such as air-conditioning.

However, because automated equipment is typically used for longer operating cycles, the reduced wear-and-

tear that results from less operator error is somewhat replaced with wear-and-tear that is associated with

56

New, R., Ball, A. and Copeland, A. (2011), Minerals and Energy Major Development Projects – April 2011 Listings, Australian Bureau of Agricultural and Resource Economics and Sciences, Australian Government, Canberra 57

Durrant-Whyte, H. (2010), The Robots are Coming: The Robotics Revolution in Australian Industry, The Warren Centre for Advanced Engineering 58



62

longer duration of continuous operation. Additionally, an automated truck, for example, is still a truck and will

have similar routine mechanical issues to a human operated truck.59

There is an argument that automated equipment will become more component oriented, with maintenance

protocols increasingly involving maintenance staff removing modules from equipment and installing new

modules from an onsite inventory, which may improve the productivity of on-site maintenance. With respect

to technology intensive components of resources industry equipment this is largely already the case. However,

common mechanical and electrical systems will still require routine and other maintenance to be conducted

on site.

THE NET IMPACT OF RESOURCE INDUSTRY ‘UNIQUE’ FACTORS ON MULTIFACTOR

PRODUCTIVITY

Figure 11 below60

compares reported multifactor productivity growth of the resources industry as reported,

with the resource depletion effect theoretically removed and with the resource depletion effect and capital

effect theoretically removed, with manufacturing, agriculture and the market sector as whole. While the

deleterious effect of the factors discussed in the previous subsections on resources industry productivity is

very real, the data presented in Figure 11 suggest that if the resources industry were not plagued by the

unique factors that affect its multifactor productivity, it would indeed be a very productive industry.

Figure 11 – Multifactor Productivity Growth 1974-75 to 2006-07: Resources Industry versus Other Sectors of the Australian Economy

59

Fisher, B. and Schnittger (2012), Autonomous and Remote Operation Technology in the Mining Industry: Benefits and Costs, BAE Economics 60

Topp, V., Soames, L., Parham, D. And Bloch, H. (2008), Productivity in the Mining Industry: Measurement and Interpretation – Productivity Commission Staff Working Paper, Productivity Commission

0

0.5

1

1.5

2

2.5

3

Resources Industry Resources Industry with Resource Depletion Effect

Removed

Resources Industry with Resource Depletion and Capital

Effect Removed

Australian Industry

Pe

rce

nt

Average Annual Growth in Multifactor Productivity, 1974 to 2006-07


63

IMPROVED RESOURCE ACCESS

Closely related to the resource depletion effect discussed in the previous section is the issue of resource

access. The CSIRO estimates that technical improvements to mining systems would assist in the conversion of

around a trillion dollars worth of currently uneconomic resources in Australia to reserves by 2030.61

A factor in

this equation is gaining cost effective access to deep and/or geotechnically challenging environments, where

OH&S risk and cost prohibit access via conventional extraction systems. Automated systems play a critical role

in extracting resources in such environments.

There are a number of resources operation types where automated systems are currently deployed primarily

to access resources that would otherwise be sub-economic or where the application of conventional

extraction systems would present an unacceptable OH&S risk. Two such examples are high-wall coal mining

and subsea oil and gas subsea production and processing systems.

High Wall Coal Mining

Coal can occur in thin seems that run from a high wall or hillside. These seams are too thin to allow

economic conventional underground mining methods, and the stripping ratio is too high to allow

conventional surface mining methods. These seams are mined using a system known as a high-wall

miner. With a high-wall mining system the power pack and control systems remain at surface. An

automated push-beam loading and drive system hydraulically propels a continuous miner along the

thin seam, with mined coal returned to surface via twin augers that are internal to the hollow push

beams. A gamma-sensor on the continuous miner guides the shearer so the shearer does not

penetrate surrounding bedrock and dilute the coal. These operations are found mostly in the United

States. However, they are also deployed in Australia. OEM’s that manufacture high Wall miners

include Terex SHM and Caterpillar.

Subsea Oil and Gas Production and Processing Systems

Subsea production and processing systems are increasingly deployed in offshore hydrocarbon

production environments as they potentially reduce the capital expenditure associated with

manufacturing, deploying and operating topside facilities, by transferring some of the production and

processing equipment that this typically located on the topside to the sea-floor. They also facilitate

the economic development of satellite deposits via increasingly long tiebacks to established host

facilities. Because subsea production and processing systems are typically deployed in very deep

water, direct human operation and inspection, maintenance and repair (IMR) is not possible. As a

result their operations are highly automated, and most routine IMR is implemented via remotely

operated vehicles (ROVs).

As resources are increasingly found in deep and challenging environments, automation to address this issue

will become increasingly commonplace. There are numerous existing mines, whose mineralization is known to

extend to depths that prohibit human access. For example, the Creighton Nickel Mine in Sundbury, Canada

extends to a depth of some 2,600 metres, where the temperatures reach 60oC and humidity approaches 100

percent. Such conditions are prohibitive to a productive workforce and present unacceptable OH&S risk.

Similarly, operations at altitude such as the Escondida mine in the Chilean Andes Mountains have taken

61

Mining Technology (2008), An Exciting Era of Automation


64

additional measures to maintain workforce productivity. Automation is likely to play an increasing role in such

operating environments.

In the longer term, the exploitation of minerals from environmentally sensitive environments such as from the

Arctic or even the seafloor will require a reduction in footprint and environmental externalities that can only

be delivered by extensive automation.

OCCUPATIONAL HEALTH AND SAFETY

As discussed in the previous section, overcoming OH&S risk is a major factor in exploiting increasingly

challenging resources in the future. However, working on minerals and oil and gas operations is already a

hazardous occupation. Many tasks are undertaken with heavy machinery and dangerous chemicals, often in

unstable, unpredictable and dangerous settings that create risk of injury or death. Many mining and petroleum

operations are located in environments characterized by harsh climatic conditions and in regions that are

prone to extreme weather events. The operations themselves often produce dust and other airborne by-

products that are potentially harmful. Furthermore, most resources projects are located in remote areas,

presenting a considerable time delay in being able to evacuate staff to primary health care facilities.

Furthermore, the lifestyle associated with working in remote locations and/or a FIFO work cycle can lead to

mental health and social behavior issues.

Automation plays a role in removing humans from working environments that are potentially hazardous.

REDUCED RELIANCE ON CONVENTIONAL RESOURCES INDUSTRY LABOUR MARKETS

The global resources industry is facing a skills and labour shortage that is expected to exacerbate in the future

as demand from China, India and other developing nations continues, and in response, existing resources

projects expand and new projects come on stream. In 2005, the CMEWA and the Minerals Council of Australia

estimated that Australian resources projects would require 70,000 more employees by 2015.62

While there will

be a requirement for additional workers throughout the workforce structure, the greatest deficiency is likely to

occur in semi-skilled and tradesperson roles in the minerals sector (approximately 70 percent of the additional

labour units required).63

Automation will reduce requirements for employees, particularly in some semi-skilled

roles where menial tasks can be automated, operators can undertake multiple tasks via remote control and

there is a reduced requirement for shifts in some functions. 64

Relocating some remote site roles to a ROC based in a capital city or other population centre also expands the

market for potential employees in the resources industry. For example a reduction in labour intensive tasks

and FIFO should provide increasing access to segments of the potential employment market for which FIFO or

62

Minerals Council of Australia and Chamber of Minerals and Energy (2006), Staffing the Supercycle: Labour Force Outlook in the Minerals Sector: 2005 to 2015 63

Lowry, D., Molloy, S. and Tan, Y. (2005), The Labour Force Outlook in the Minerals Resources Sector, National Institute of Labour Studies, Flinders University, Adelaide 64



65

physical labour is a prohibitive factor, including making the industry attractive to more women.65

This is

evidenced to an extent by the fact that operational sites that are in close proximity to major population

centres report that they are less affected by the skills shortage than those that are in remote locations.

Historically, there has been a reasonable prediction that this labour shortage will be a major driver of rapid

adoption of automation. While the automation will indeed alleviate the skills shortage to some extent, it is

unlikely, for reasons discussed in a subsequent section of this report, that automation will be adopted

extensively enough for it to address short term issues. Furthermore, some operations that have adopted high

levels of automation have significantly increased production. As a result, while the workforce structure of

those operations has changed, total head-count has remained relatively stable or even increased as

employment in other roles expands to cope with the increased production.

REDUCED ENVIRONMENTAL EXTERNALITIES

Environmental benefits generally arise because machines are operated in a more precise and efficient manner

so that fewer consumables and less energy are used in the process. For example, intelligent ventilation

systems can adjust requirements depending on the number and location of personnel.66

Furthermore,

automation has the potential to reduce the footprint of operations. Control of mining systems from a ROC

reduces the need for land intensive onsite worker accommodation, and automation systems such as key-hole

mining potentially reduce the operational footprint of operations.

DETRACTORS TO ADOPTION OF AUTOMATION IN THE AUSTRALIAN RESOURCES

INDUSTRY

As there are general drivers of adoption of automation in the resources industry, there are also general

detractors. As with the general drivers, the degree to which these general detractors impact on a decision to

adopt automation varies considerably among operations, simply by virtue of the diversity of the operations

that comprise the resources industry. The most commonly cited detractors are the impact of automation on

project economics by virtue of a resulting higher capital cost and switching costs, and as a result on financing

risk, the impact of related technical risk on project finance risk and operational risk, the impact of required

organizational change on operational risk and the specific operational risks that arise in an automated

environment. These factors and their relationships are illustrated conceptually in Figure 12 below and

described in detail in the following subsections.

65

Fisher, B. and Schnittger (2012), Autonomous and Remote Operation Technology in the Mining Industry: Benefits and Costs, BAE Economics 66



66

Figure 12 - General Detractors to a Decision to Adopt Automation in the Resources Industry

HIGHER CAPITAL INVESTMENT AND IMPACT ON PROJECT ECONOMICS AND SWITCHING

COSTS

The deployment of automated systems for most resources operations requires a considerable level of

customization and automated equipment and systems are significant capital investment items in their own-

right. This adds significantly to the amount of capital that is required for the project and directly impacts on

the project’s Net Present Value (NPV).

This significant investment presents challenges to both brownfields and greenfields operations. In commodity

price down-cycles pressure is placed on new projects to minimize capital expenditure in order to improve

project NPVs, which significantly reduces the appetite for capital intensive automation systems, particularly in

light of some of the technical uncertainties mentioned in the following section. In times of high commodity

prices, the main focus of project proponents is to get to production as quickly and with as little risk as possible

in order to capitalize on the higher prices and as such, there is limited appetite for extended development

time, cost and risk that can be associated with new automation technologies. Automation system investment

decisions pertaining to brownfields operations face the same challenges, with the additional issue of switching

costs. Because most existing sites are designed for conventional operational processes, the investment

required to change operational processes and existing equipment for an automated environment can be

prohibitive.

Impact on ProjectEconomics

Impact of higher capital cost on NPVfor greenfields projects

Impact of switching costs on NPV forbrownfields projects

Technology RiskMany new technologies that haven’tbeen extensively trialled in resourcesindustry applications

Risk associated with equipment andautomation OEM support integration

New OperationalRisks

Over-reliance on automated processes

Passive operator risk

Over-reliance on systems redundancyapproach of OHS

Organisational Change

New roles and work patternsMulti-site integrationNew modes of communicationNew reward systemsWorkforce retrainingNew leadership models

Project Finance Risk

Operational Risk

Operational Risk


67

Mine/reservoir life is also a significant factor in the economics associated with a decision to invest in

automation. Projects with longer lives have the benefit of amortising the investment over a longer period of

time.

TECHNOLOGICAL UNCERTAINTY

While technology risk is not the biggest challenge facing most organizations, with respect to most elements of

an automated system, some technologies that are deployed in a comprehensive automation system are

relatively new and not extensively trialed in a resources operation environment. Examples of specific technical

and infrastructure challenges associated with automated systems in a resources operation include:

Implementing reliable data networks over large geographical distance and out to remote locations

can be problematic;

While automated loaders that identify ore based on blast block data are reasonably reliable,

automated loaders using sensing technology to estimate the composition of ore still require

considerable development;

While automated LHDs are commercially available, automation of the dig cycle is a problem in

anything but very well broken rock; and

Automated blasting is still proving challenging because of the sensitivity of detonators and boosters,

and the risk that sensitivity presents to high value automated drilling and blasting equipment.

For automation to deliver the benefits discussed in a previous section of this report, and thus deliver the

necessary return on investment, the system must maintain a certain defined minimum level of performance

and reliability. Technical uncertainty associated with issues like those mentioned above places this at risk.

More importantly, failure of a component of an automated system to meet performance and reliability criteria

can result in decreased production, or in the worse case, operational down-time, both of which have a

negative impact on project NPV. This issues can be exacerbated where maintenance costs and reliability

becomes problematic as a result of being required to deal with separate equipment and automation systems

OEMs.

As such, project managers and project financiers can be reluctant to take on the technology risk associated

with new automation technologies.

ORGANISATIONAL CHANGE

The implementation of extensive automation systems in a resources operation that is based on conventional

operational methods requires a significant exercise in organizational change and development, as its impacts

pervade the entire operation. Key changes include the following:

New Roles

Most automated systems will result in a reduction in the number of manual, repetitive, heavy labour

and/or hazardous jobs, and an increase in the number knowledge worker and technician roles. This

implies, not only a shift in the skills profile of the workforce but the demographic of the workforce. It

is likely that the workforce will evolve to include a more proportionate gender balance and an


68

increase in the portion of technicians, para-professionals and professionals in the workforce. New

functions and management roles that are more akin to manufacturing or logistics process

optimization will become key functions in the operation.

New Work Patterns

The automated system may result in a reduction of the FIFO workforce, with many roles becoming

less shift-oriented and moving to a ‘9 to 5’ metropolitan based role. Problem solving will become a

more operations-wide, multi-disciplinary and data intensive analytical exercise, in many cases. Teams

will become increasingly cross-operation and cross-function oriented, often involving multiple

locations and jurisdictions.

Unprecedented Multi-site Integration

Operations where the automation system spans multiple sites, and is at least in part centrally

controlled from an ROC, will require new forms of team structure and team dynamics and new

methods and standards for intra and inter team communications. For example, in a system with

automated haulage trucks, crews working in, say, the pit will no longer be communicating with a

driver who they live and socialize with on site, but rather an operator who is overseeing the entire

haulage fleet from a remote location, possibly even in another country. This in-turn implies a

potential need for greater cultural awareness in the workforce.

New Reward Systems

In many multi-operation companies, reward systems for staff are often focused on KPIs pertaining to

the specific site on which they work, such as improvement in site throughput. For automation to

achieve all-of-operation optimization, KPIs and reward systems may need to be adjusted to optimize

whole-of-operation net performance.

Workforce Retraining and Professional Development

Developing the required skills, including soft-skills that will be required within the workforce will likely

involve reasonable investment in workforce training and professional development across all tiers of

the organization. This is likely to involve external training providers as well as internally developed

operations policy programs.

New Leadership Models

As with all change programs, the implementation of an extensive automated system is likely to

encounter at least initial resistance. Some operations will have a well entrenched operational culture

and the implementation of an extensive automation system is likely to invoke attitudes of ‘that is not

how we mine’. The fact that the implementation of an extensive automated system is an exercise that

pervades the entire operation, many current automation programs are being driven top down from

senior management67

, with project sponsorship residing at president level. As the system is

implemented and becomes operational, the workforce will need to come to terms with an increasing

presence in the leadership team of management that may not have extensive resources industry

experience and may have backgrounds from very different industries such as manufacturing, ICT

systems integration or the military.

Organisational change is a resource intensive and relatively uncertain process that carries operational risk.

67

Dudly, J., McAree, R. And Lever, P. (2009), Bridging the Automation Skills Gap: Why the Australian Resources Sector Should Support and Automation Skills Development Program, CRC Mining


69

NEW OPERATIONAL RISKS

The implementation of an automated system significantly changes operational tasks, job roles and working

environments and involves a very different interface between workers and the operation. Experience from

other industries that implemented automated systems suggests this can lead to a new suite of operational

risks that the operation may not be accustomed to managing. For example:

Passive operators of an automated system may lose situational awareness and over time become

deskilled and unable to take appropriate corrective action in the event of equipment malfunction or

unexpected events; and

The potential to over-rely on automation creates the risk for monitoring error, when warning systems

are ignored or turned off or when complex systems cause operators to overload.

These issues need to be addressed by competent training and professional development programs that

support staff during the implementation of the automated system and on an ongoing basis.

PLANNING FOR AUTOMATION

As highlighted in the previous discussion, the implementation of extensive automation in a resources

operation is a complex process. Research into historical automation programs has highlighted key issues that

management should consider when planning implementation of an automation program: 68

An extensive automation system involves implementing and integrating a wide range of technologies.

Managers need to be cautious not to proceed to a ‘solution mode’ until technical, human and

organization architecture issues associated with these technologies and their integration is well

understood and planned for;

Ensuring that the resulting architecture solution addresses all the relevant aspects of people, process,

information, technology and culture, and that the process of arriving at an architecture has not been

solely technology driven;

Ensure that internal support for the value proposition of automation is acquired at all levels of the

organization through the transformation program by engaging relevant stakeholders through active

participation in the entire process;

Through training and leadership, ensure that the business process and behavioural changes necessary

for a more collaborative operational environment are effected and become the operating norm; and

Instill an organizational culture of having a willingness to learn from other industries and to partner

with vendors and services providers who already have the experience.

AUSTRALIAN RESOURCES INDUSTRY AND ADOPTION OF NEW TECHNOLOGY

68

Farrely, C. (2007), ‘Remote operations centres, lesions from other industries’, Australian Mining Technology Conference


70

Resources industry operations have unique common characteristics with respect to the adoption of new

technology:

Much of the value chain involves large long term investment in capital equipment, the Net Present

Value’s of which are sensitive to unscheduled downtime. As such operators and project financiers are

very reluctant to expose those assets to uncertainty associated with technology risk;

The sunk cost involved in that capital equipment provides limited scope for substantial process

change over the life of a project69

; and

Because many projects are characterised by large process throughputs, incremental improvements to

efficiency can have a significant financial impact.70

Despite the entire resources industry sharing these common characteristics, the oil and gas industry has been

a far more rapid implementer of new technology than the minerals industry. As discussed below, the higher

propensity for the oil and gas industry to invest in technology development and deployment has most likely

been a result of the more rapid depletion of its global resources and the need to develop technology that

enables entry into significantly more challenging exploration, production and processing frontiers and the

more globally integrated nature of the oil and gas industry’s supply chain.

MINERALS INDUSTRY

As discussed in a previous section of this report, growth of the minerals industry has been a function of

technology development. However, globally the minerals industry is a relatively conservative adopter of new

technologies often requiring extensive piloting processes before a new technology is implemented or only

considering new technology where the associated platform technology or derivative of the platform

technology has been successfully deployed in similar applications in other industries.

The Australian minerals industry is often criticized as being a particularly late adopter of new technologies.

While, the Australian industry has been a world-leader in some aspects of minerals industry technology

development and deployment, there are many instances where the Australian industry has not adopted new

technologies until they have been extensively demonstrated in practice in other minerals industries or

extensively piloted in the Australian industry. For example, Figure 13 below71

suggests that from a sample of

19 technologies used in the underground coal industry, on average these technologies had been in operation

for 7 years before being used in the Australian industry and that they required an average of 13 years of trials

in Australia before they were generally accepted by the Australian minerals industry.

69

Allen Consulting Group (2009), Earth Resources National Innovation Strategy (ERNIS): Scoping Study, Victorian Department of Primary Industries 70

Dry, R., Batterham, R., Bates, C. and Price, D. (2002), ‘Direct smelting: why have so few made it’, AATSE Focus, July/August, 8-17 71

McCarthy, P., New Mining Technology Takes Time, AMC Consultants


71

Figure 13 - Historical Adoption of Certain Underground Mining Technologies by the Australian Mining Industry

When the relatively early stage of development of field robotics technology is taken into account, there is

some evidence that the industry is embarking on a relatively rapid adoption trajectory. Some sectors of the

industry seem to be moving quickly to catch-up with other industries on the adoption of automation.72

OIL AND GAS INDUSTRY

The oil and gas industry is much younger than the mining industry. As oil was extracted at rapid rates to feed

the industrial revolution, exploration and production environments rapidly moved into more challenging

geologies. Increasingly challenging onshore environments and the emergence of the significantly more

technical offshore industry has forced the oil and gas industry to invest heavily in technology development and

adopt a greater level of technology risk than the mining industry. Much of this investment has been

undertaken by an R&D intensive global oil and gas services and supplies sector.

The rapid development and uptake of technology in the oil and gas industry is illustrated in Figure 14 below,

which illustrates the timing of the key new technologies that have facilitated the establishment and growth of

the onshore, offshore and deepwater sectors of the oil and gas industry over the short period of approximately

150 years. 73

72

Business-Higher Education Round Table (2011), ICT, Technology, Skills – The Changing Face of Mine Operations and Management, Position Paper Number 15 73

Leffler, W., Pattarozzi, R. And Sterling, G. (2011), Deepwater Petroleum Exploration & Production, 2nd

Ed., Penwell, Oklahoma


72

Figure 14 - Technology Development in the Oil and Gas Industry

The rapid development and deployment of new

technology in the oil and gas industry is particularly

noteable in the offshore sector. Arguably, the offshore oil

and gas industry commenced in 1947 when Kerr-McGee

completed the first successful offshore well in the Gulf of

Mexico in 4.6 metres of water.74

The rapid development

of offshore and deepwater technologies from this point is

quite remarkable, particularly given the extreme technical

complexity of producing from very deepwater. Figure 15

below shows increasing depths achieved by Petrobas

discoveries between the period 1977 and 1999.75

74

Bai, Y. And Bau, Q. (2012), Subsea Engineering Handbook, Elsevier, Oxford 75

Leffler, W., Pattarozzi, R. And Sterling, G. (2011), Deepwater Petroleum Exploration & Production, 2nd

Ed., Penwell, Oklahoma

1860

Drake’s well

Diamond bits

Geological surveysDrilling mud

Summerland

SeismicCreole platform

Submersibles

Horizontal drillingSemi-submersibles

Drill ships ROVs

Subsea wells

TLPs

FPSOs

3D seismic

Catemary risers

Bright spotsFrac Pack completions

J-Lay pipelines

S-Lay Pipelines

Flexible risers

Onshore

Offshore

Deepwater

1900

Rotary drilling

1940 1980 2020

Tech

no

logy

Ch

ange

‘Going into deepwater demands so much of

so many that few individuals can grasp all of

the intricate details and technical challenges

that have to be overcome’

- Jack E. Little, President and CEO

(retired)

Shell Oil Company, October 18,

20101


73

Figure 15 - Progressive Depth of Petrobas Wells in Offshore Brazil

STATUS AND TRAJECTORY OF ADOPTION OF AUTOMATION IN SPECIFIC OPERATION

TYPES AND SECTORS THAT COMPRISE THE AUSTRALIAN RESOURCES INDUSTRY

In 2009, Kinetic Group (formerly the Mining Industry Skills Centre) estimated that the strongest growth in

uptake of automation by Australian resources industry operations would occur over the next decade.76

However, as discussed throughout this report, the compelling case for automation is operation specific. In this

sense it is a similar to the automation adoption environment in agriculture as discussed in the case study in a

previous section of this report.

While there is already a high degree of automation in the oil and gas industry, and there is likely to be

accelerated adoption of automated mining systems in some large operations in specific sectors, namely coal

and iron ore, accelerated adoption is unlikely to occur across all sectors of the Australian resources industry or

even within all operations in the iron ore and coal sectors.

Indeed some industry commentators remain pessimistic as to the speed at which automation will be adopted

across the industry, suggesting that it is unlikely that a transition to a fully automated environment will be

possible unless the industry first passes through an intermediate phase that enables the development of

platform technologies that satisfy reliability expectations, a process that is likely to take at least two decades.77

This section of the report discusses the case for adoption of automation according firstly to specific types of

resources operations and then within specific sectors of the Australian resources industry.

76

Mining Industry Skills Centre, Automation Skills Strategy Formation 77


0

200

400

600

800

1000

1200

1400

1600

1800

2000

Me

tre

s o

f W

ate

r D

ep

th

Petrobas Discoveries and Drilling Records

Series1


74

TYPE OF RESOURCES OPERATION

While the case for adoption of automation is most certainly company and site specific, we can make some

slightly more specific observations at a resources operations type level. This section discusses the extent of

adoption of various automation technologies across minerals exploration, offshore oil and gas exploration,

open pit mining, underground mining, offshore oil and gas production and subsea oil and gas production and

processing.

MINERALS EXPLORATION

Remote sensing is used extensively for reconnaissance exploration that is designed to identify anomalies for

further exploration. The acquisition of data from satellites is obviously a highly automated process. However,

the process of generating images and other information from this data is becoming increasingly automated

through the application of sophisticated algorithms and access to increasing computing power.

Increasingly Unmanned Aerial Vehicles (UAVs) are used for collecting geophysical data through procedures

such as aeromagnetic surveys.78

UAVs offer a number of advantages including cost and safety. They can also

be operated so that they produce higher quality data.

Field sampling methods such as soil and outcrop geochemistry and vegetation sampling remain highly manual

process and will most likely remain so, as the identification of suitable samples requires the expert judgment

of a geoscientist.

Drill rigs that are used in exploration remain primarily manually operated pieces of equipment, requiring a drill

crew to install a rig, collar a hole, progressively change drill strings as the hole progresses, take and store drill

cuttings or core and resolve problems such as a stuck drill-bit. The most repetitive and physical task on an

exploration drill rig is arguably changing drill strings. This is a systematic process that is highly suitable to

automation. However, a key design specification in drill rigs is weight. Weight is a key factor in determining the

effectiveness of drilling in some rigs and in the transportability and terrain applications of others. For example,

RC rigs are required to be heavier than diamond core rigs to advance a less effective cutting piece. However,

they cannot be too heavy so as to become challenging to transport or are rendered ineffective on soft or wet

terrain. Diamond core rigs are required to remain relatively light so that they can be easily transported into

difficult terrain (dense vegetation, hillsides etc) or used on soft or wet terrain. Thus, while the application of

automation to an exploration drill rig may reduce the number of crew required to operate the rig and present

OH&S benefits, the automation equipment will substantially change the weight profile of the drill rig. It may

also increase its footprint, which will be problematic in environmentally or culturally sensitive areas.

The biggest time lag in the minerals exploration process is the assay process, the delay in which is caused

primarily by the need to physically pack and send mineral samples to a centralized laboratory for assaying. For

greenfields exploration companies this causes substantial delays in announcing results to investors and in

planning ongoing exploration. The problem is exacerbated in the case of mines that have very high production

rates, as it causes delays in converting resources to reserves, which has a negative impact on mine planning

efficiency and maintaining sustainability or growth in reserves for investor reporting purposes. As such,

78

Finkelstein, R., The Ubiquitous UAV, Robotic Technology


75

considerable research and development is occurring in the area of real-time assaying and down-hole sensing in

an attempt to reduce reliance on the conventional laboratory assaying process.

There is a school of thought that there is much scope for considerable advancement in the overall way in

which minerals exploration is undertaken. Exploration drilling for offshore oil and gas is a very expensive

exercise with deepwater wells costing in the vicinity of US$40 to US$100 million79

. As a result the oil and gas

industry has developed very sophisticated drill targeting methods based on seismic and other geophysical

methods. This has resulted in relatively high well success rates. As minerals exploration advances into deeper,

more complex geologies, there is perhaps scope for it to adapt some of these methods to better target drilling

operations.

OFFSHORE PETROLEUM EXPLORATION

The acquisition of marine seismic is undertaken by specialised manned seismic survey vessels that have some

degree of automation around the deployment of towed geophones and source equipment. The turnaround

time from data acquisition to the production of a seismic image and other data that can be interpreted by a

geophysicist has historically been protracted. However, increasingly advanced algorithms and computing

power is facilitating at least a degree of on-board processing.

Exploration drill rigs, while normally manned, have a high level of automation with repetitive processes such as

insertion of drill strings and casing relatively automated processes on most rigs.

OPEN PIT MINING

Drilling and blasting is largely a repetitive task that involves positioning drill rigs over a predetermined position

according to a mine plan, drilling a relatively shallow hole, inserting a predetermined charge detonator and

booster and moving to the next charge site. It is also a task that has some associated OH&S risk. As such, it is a

process for which automation can deliver benefits. Considerable investment has gone into automating this

process for application particularly in high volume operations. The key challenge is the sensitivity of

detonators, and the risk this presents to expensive automated equipment.

Automated loaders that determine load sequencing from blast block information that is produced from

development drilling and linked to a blast block through mine planning software area seem to be a reliable

aspect of automation in the value chain. However, loaders that determine the ore characteristics of load

through sensor technology still require significant development.

The main focus of automation, and perhaps its most extensive application to date in open pit operations, is in

haulage. Automated haulage trucks of been operating at a number of trial sites around the world for some

time including iron ore mines in the Pilbara, diamond mines in South Africa80

and base metal operations in

North and South America. Haulage truck OEMs such as Komatsu and Caterpillar have been conducting

significant internal development programs and programs in collaboration with major mining companies to

develop this technology for some time, with many of the initial challenges such as haul road condition

79

Smith, M (2008), ‘Escalating offshore expenditure, production expected’, Energyfiles 80



76

optimization and monitoring either having been addressed or in advance stages of solution development. In

large bulk commodity operations haulage and loading automation has extended to automated ship loaders

and other port facilities and is advancing toward the deployment of driverless trains.

Automated haulage can also be applied to alleviate OH&S risk in deep and steep pits that are located in harsh

conditions such as high altitude or areas prone to very high temperatures.

Development work has also been undertaken with the view to replacing haulage truck fleets with a conveyor

operation. However, to date it would seem that capital costs and the resulting reduction in operation flexibility

are prohibitive.

All other factors being equal, the greater the portion of total cost that is attributable to haulage, the more

critical efficient haulage is to overall economics, and the greater the OH&S risks associated with manual

operation of the pit, the more compelling automated haulage is. It would seem that in many cases the case for

automated haulage in open pit operations is currently not adequately compelling.

UNDERGROUND MINING

The main benefit of automation in an underground mine is typically the reduction of OH&S risks.81

Underground mines are inherently dangerous environments and as underground operations progress into

deeper more geotechnically challenging environments, this risk will increase. Solutions to mitigate that risk will

be found only in new technology. In most operations, risks generated by the geotechnical environment such as

collapses and rock bursts caused by induced seismicity are the main OH&S threat. However, in underground

coal operations the risk is exacerbated by the fact a volatile substance is being mined. The vast majority of

OH&S incidents in underground mines occur at the mine-face where there is an intensity of operating heavy

machinery and new cuttings advancing in the absence of stabilised roof and wall supports. In underground coal

mines where the deposit geology permits, highly automated long-wall mining systems are commonplace.

Based on existing technology, underground coal mining using long-wall mining systems is only viable because

of the relatively uniform nature of underground coals seams. In underground geologies that are less uniform,

the adaptation of manned continuous miners to remote controlled units that remove humans from the mine-

face are being developed. However, in more challenging underground ore bodies, drilling and blasting remains

the norm.

There have only been negligible labour savings, if any at all, from the increasing automation of underground

mines. Typically 50-60% of underground employees are direct operators of equipment. Any labour saving

through automation will be largely offset by the need for specialised maintenance support.82

However, there is

significant evidence of meaningful productivity improvements. The productivity improvements achieved from

long-wall mining in the coal industry have been substantial and the application of automated LHD at Olympic

Dam have produced an extra 2.4 hours per shift of production by operating the loaders manually and then

swapping to automated mode during shift changes and meal breaks.

81

Noort, D. and McCarthy, P. (2009), Automated Underground Mining, International Mining January Edition 82



77

OFFSHORE PETROLEUM PRODUCTION

PLATFORM, FPSO AND FLNG BASED PRODUCTION AND PROCESSING

Automation is more advanced in the O&G industry than in the minerals industry. There are a number of key

reasons for this, including:

The liquid and gas phase processing nature of petroleum operations lend themselves more readily to

systems integration and automated processing than does hard rock mining;

The rapid advancement of production facilities into what are known in the industry as 4D (dull,

distant, dirty and dangerous) environments as well to offshore distances that are beyond the range of

current helicopter technology has driven investment in technologies that support not-normally

manned facilities; and

In many elements of the offshore operating environment a degree of automation is a technical

necessity because humans simply cannot physically or at least safely enter the operating

environment.

In recent years, it has been necessary to seek oil and gas in increasingly remote and hostile environments, as

most of the easily-accessible fields are depleted or nearing depletion. Novel technical solutions, work practices

and business models have been developed to enable safe operation in these remote locations. The industry

has for some time, by technical necessity used robotic and remotely controlled technology as an enabler of

various inspection, maintenance and repair (IMR) tasks in next-generation, normally unmanned production

facilities and on the seafloor.

It is important to note that from a systems and cultural perspective the step from a manned offshore

production rig to a normally unmanned production rig is less significant than the change from a manned mine

to an automated mine, simply because even in the case of manned production rigs, most systems are highly

automated and the main role of operational staff is to address exceptions.

Semi-submersible rigs, Floating Production, Storage and Offloading (FPSOs) and Floating LNG (FLNG) facilities

are connected to highly automated subsea production and sometimes processing facilities (see next section)

and deploy highly automated mooring systems to keep the floating facility in place.

While it is notable that existing decentralised automation equipment is used today for remote operations of

modern petrochemical facilities, it is estimated that complete automation of O&G facilities requires an

automation system capable of around 1,000 additional operations that are currently performed manually.,

including valve manipulation, sample-taking, scraper handling, daily inspection rounds and maintenance work

such as instrument replacement or cleaning.83

There is a level of robustness, accuracy and reliability required

from automated systems by the O&G industry that is very high. A 90 percent technical competency rate is

below the acceptance rate for real world deployment in oil and gas facilities that operate in association with

live hydrocarbon pipes. 84

Today, field operators and maintenance staff still need to enter the hazardous process areas to perform

special inspection, testing and calibration and maintenance tasks. Increasingly such tasks will be undertaken by

83

Anisi, D., Perrson, E and Heyer, C. (xxx), Real-world Demonstration of Sensor Based Robotic Automation in Oil and Gas Facilities 84

Skourup, C. (xx), Robotics for remote oil and gas operations, ABB Strategic R&D, Norway


78

robotic technologies85

, such as UAVs and ROVs. Indeed, Subsea 7 are in the process of commercializing a pre-

programmable autonomous vehicle that can complete pre-programmed short-term inspection and routine

maintenance missions. However, long- range ROV’s that can be deployed for extended periods of time to

perform routine maintenance on subsea systems components require significant further development, with

the major challenges being data-download and battery life.

Other immediate areas of automation are likely to address issues such as valve stroking or rapid construction

of modularized facilities by linking RFID tags on components with engineering drawings.

Because automation and remote control have been entrenched technologies in the oil and gas industry for

some time, management in resources is increasingly on organizational processes. Skill sets and work

orientation in what is already a highly automated environment becomes process oriented and revolve around

systems such as Lean Six Sigma.

Integrated ROCs are well established in the oil and gas industry with most major oil and gas companies

including Woodside, BP, Statoil, ConocoPhillips, Saudi Amarco and Petrobas operating some facilities from a

centralized ROC. ROCs have delivered significant benefits to operations including:

Reduced facilities manning, improved OH&S and improved environmental management;

Improved integrity and reliability of wells and facilities;

Optimisation of reservoir depletion and increased ultimate recovery;

Improved efficiency and reduced operating costs;

Improved quality and more timely decision making;

Improved staff satisfaction, retention and attraction; and

Sustained culture of continuous improvement.

SUBSEA PRODUCTION AND PROCESSING

Subsea field development was born in the early 1970s via a concept of placing wellhead and production

equipment on the seabed with some or all of the components encapsulated in a sealed chamber, with the

hydrocarbon produced flowing from the well to a nearby processing facility, either on land or on an existing

offshore platform.86

Over the past 40 years, subsea production systems have advanced from manually

operated systems deployed in shallow water (less than 300 metres), to systems capable of operating with high

levels of automation and remote control in depths of up to 3,000 metres. 87

These systems can involve multiple

subsea trees that are linked to a central subsea manifold which feeds the hydrocarbons back to a host facility

via a riser.

Subsea processing is complementary to subsea production and includes any subsea equipment deployed for

the purposes of handling and treating hydrocarbon streams produced from subsea production equipment for

the purposes of mitigating flow assurance issues between the subsea production system and the host facility.

Subsea processes include boosting, separation, solids management, heat exchanging, gas treatment and

chemical injection.88

Locating such processes on the seafloor has a number of inherent benefits including:

85

Skourup, C. (xx), Robotics for remote oil and gas operations, ABB Strategic R&D, Norway 86



Bai, Y. And Bau, Q. (2012), Subsea Engineering Handbook, Elsevier, Oxford


79

Enabling of smaller topsides as equipment that is typically located on the topside is transferred to the

seafloor, reducing overall field capital expenditure;

Accelerated or increased production and increased recovery from the field;

Enabling the economic development of marginal fields, particularly those located in deep and ultra-

deep water, or where long-tie backs to a host facility are required; and

Enabling the tie-in of satellite developments into existing infrastructure;

As illustrated in Figure 16 below, the development of subsea processing technologies has been rapid over the

past fifteen or so years.89

Figure 16 - Development of Subsea Processing Technology

Subsea trees and manifolds, once installed are largely static devices, with the choke being the most dynamic

component and this is rarely adjusted. Subsea processing equipment is significantly more complicated and by

its very nature, subsea processing mandates a high level of automation.

The design of subsea processing equipment focuses on simplicity and durability, with moving parts kept to a

minimum90

, as moving parts in a saline, high-pressure environment present mechanical reliability challenges.

Furthermore, subsea processing processes are often required to perform within very tight bands of variation

and because they are at depth where cost effective servicing options are limited, they must maintain

performance for very long periods of time. For example, the water re-injection specifications for the Marlim

Field offshore Brazil are 100ppm of oil and no more than 10ppm of sand. The subsea separation system that

maintains streams with these specifications must operate reliably for five years without major maintenance

requirements.91

THE CASE FOR ADOPTION OF AUTOMATION IN SPECIFIC SECTORS – SOME EXAMPLES

Some more specific observations can also be made with respect to the status of adoption and specific issues

facing adoption of automation for sectors of the resources industry. To date, the adoption of automation

within the mining industry has been most prolific in the bulk commodity sectors, particularly with respect to

iron ore and coal, with adoption across other sectors being more sporadic. This section discusses adoption and

adoption issues in coal, iron ore and alumina bauxite sectors, as well as some of the issues facing other sectors,

using actual cases as examples.

89


Rassenfoss, S. (2011), ‘Growing offshore water production pushes search for subsea solutions’, Journal of Petroleum Technology, August Issue 91

Rassenfoss, S. (2011), ‘Growing offshore water production pushes search for subsea solutions’, Journal of Petroleum Technology, August Issue

1996 2002 2006 2008 2010

MultiphaseBoosting

Water RemovalWater Re-injection

Gas/LiquidSeparation &

Solids Management

Water/GasCompression

3-Phase SeparationGas CompressionAdvanced Control


80

COAL INDUSTRY

Of the sectors that comprise the minerals industry, the underground coal mining sector is the most

automated. The level of automation ranges includes almost totally automated and remote controlled high-wall

mining systems (see previous section of this report) and highly automated long-wall mining systems. In

Australia, the underground coal mining industry, the Australian Coal Association Research Program (ACARP),

CRC Mining and the CSIRO have undertaken considerable collaborative research in the automation of long-wall

mining systems as well as technologies that facilitate rapid underground roadway development.

Long-wall mining systems have been the focus on innovation for some time. This was achieved by partial

automation of the continuous mining process by automating one easily definable machine operation and task

at a time. Over time, this has resulted in a highly automated overall process. 92

Besides the obvious OH&S benefits associated with removing personnel from the coal-face, automation

associated with long-wall mining has resulted in significant productivity gains. In particular the automation and

inertial navigation of the shearer has resulted in more data being generated on how the face is mined,

facilitating automated face-alignment and automated retreat. It has been estimated that this alone has

improved productivity by around 5 percent.

Experience from operators that have gradually increased the level of automation in underground coal mining

operations suggests that its implementation is a journey in cultural change and significant and ongoing re-

training. This transforms an initially resistant workforce to one that embraces and is excited about automation

and remote control technology. In some experiences the introduction of automation in long-wall mining has

increased production, resulting in higher employee number, albeit the productivity per labour unit has

improved.

IRON ORE INDUSTRY

While the underground coal industry seems to have the highest current intensity of automation among the

sectors that comprise the Australian mining industry, it is the Pilbara iron ore industry that is embarking on the

most rapid automation program. Rio Tinto and, to a lesser extent BHP Billiton and FMG are in the process of

making considerable investments in the automation of their Pilbara iron ore operations from drilling and

blasting through to ship loading. The operations are comprised of multiple mines that are interconnected by a

rail network that expands across the Pilbara region of Western Australia and connects the mines to export

ports in Port Hedland and Dampier. They are essentially, large, complex, bulk commodity logistics operations.

While the OH&S issues in this operating environment are perhaps less confronting than those in the

underground coal industry, the significant improvements in productivity that can be gained by automating and

optimizing the operation of the logistics network are significant, particularly where the operators owns and

operates all of the infrastructure from pit to port.

RIO TINTO FUTURE MINE PROJECT

Rio Tinto’s Pilbara operations automation program, the Future Mine Project, is perhaps the largest single

mining automation program in the world, and certainly the most publicized.

92



81

The program has revolved around the Company’s West Angelas Pit A operation, which has been automated in

a number of new and fundamental ways. The West Angelas Pit A trial is a substantial commercial scale

automation trial producing approximately 25 million tonnes of iron ore per annum. The automated operation

combines the Komatsu autonomous truck system with Rio Tinto’s autonomous drills and autonomous drill-

blast expert system. The trial has been running for well over a year with a view to developing a Pilbara

operations automation template which will be deployed across the next generation of iron ore mines in the

Rio Tinto’s Pilbara network.93

The expansion of Rio Tinto’s automation program has commenced with plans to deploy 150 Komatsu

automated trucks at the Company’s Yandi and Brockman 2 operations over the next 12 to 18 months.

Additionally, Rio Tinto is investing US$518 million in driverless trains, with the company set to run the world’s

first automated long-distance heavy-haul rail network. Known as ‘Autohaul’, Rio Tinto’s automated train

program is scheduled for completion in 2015, a year after the first train is delivered. On its 1,500 kilometre rail

network, Rio Tinto currently operates 41 trains from mines to ports, comprising 148 locomotives and 9,400

iron ore cars. The automation of the rail network will allow Rio Tinto to expand Pilbara production capacity

without needing to make a substantial investment in additional trains by providing greater flexibility in train

scheduling and removing the need for driver shift changes.94

The Pit A trial and the roll-out and operations of Rio Tinto’s automated Pilbara network are being managed by

a Remote Operations Centre (ROC) located in Perth. This facility has 320 staff and is located at Perth Airport so

that the ROC is on the same energy grid as the Perth Airport traffic control system. This is a protected grid with

a 9,000 litre diesel tank on site to run back-up generators should a power failure eventuate.95

Rio Tinto has also entered into technology development partnerships with a view to developing systems for

the automation of other aspects of its global operations. For example, Rio Tinto is in partnership with:

TOMRA, a leading supplier of automated sensor-based systems used in recycling and food processing.

The partnership with this Norwegian company is aimed at developing commercial-scale systems for

separating minerals from rock waste. This work will include scaling up Rio Tinto’s ore and copper

sorting technologies which extract saleable ore from waste rock with a capability of processing up to

1,000 tonnes of rock per hour.

UK-based e2V to develop machines to improve the efficiency of mineral recovery from previously

discarded ore.

Atlas Copco to develop new shaft and tunnel boring systems that significantly reduce the time to

excavate underground (up to 10 metres per day which is approximately twice the current rate).

BHP BILLITON

BHP Billiton is also executing a largely confidential internal automation program called the Next Generation

Mining Program. This program has senior management sponsorship, and is examining the automation of

equipment throughout the value-chain for various commodity operations. Most of this work focuses on

automation processes that can be enabled through technologies that are commercially available today.

However, part of the program is also examining the application of future horizon technologies.

93

CSIRO (2009), Earthmatters, Issue 19 94

Australian Journal of Mining (2012), Rio Tinto Ramps Up Automation Efforts, February Online Edition 95

Dyson, N. (2012), ‘Robominer’, Mining Monthly, April Edition


82

BHP Billiton’s metallurgical coal group has been trialing automated drills for some time and an energy coal

operation in the United States has been trailing automated haul trucks.

OTHER PILBARA IRON ORE OPERATORS

Fortescue Metals Group has been working on an automated haulage program in conjunction with Westrac. It

would appear that other Pilbara iron ore operations may not have scale that is adequate to render investment

in extensive automation immediately compelling.

ALUMINA-BAUXITE INDUSTRY

Bauxite mines in Western Australia tend to be very large operations, with long haulage roads connecting

satellite deposits to central ROM stockpiles and long conveyor belts that deliver bauxite from the ROM

stockpiles to refineries. For example, at Alcoa’s Huntley operation, the average haul road distances is 8

kilometres with some roads reaching 17 to 18 kilometres in length. In such operations, haulage can account for

as much as 50 percent of total production labour hours, creating a prima facie compelling case for automated

haulage. Furthermore, the processes downstream from the mine are highly automated. For example, the

conveyor process that delivers ore from the ROM stockpiles, that move at approximately 8.5 metres per

second are PLC controlled. Companies are currently investigating ways of automating certain maintenance

procedures pertaining to the belt. Additionally, the Bayer Process itself is highly automated.

However, a number of challenges exist to automation in bauxite mines:

First and foremost, mining operations only account for around 20 percent of the total cost of

producing alumina and as such, the whole of operation investment case for automated haul trucks is

less compelling;

Haul roads in Western Australian bauxite operations transect large areas of natural bush land and in

order to reduce capital cost and footprint, they are a narrow design. This creates a much wider range

and greater frequency of potential collision events such as wildlife and hikers crossing the roads,

variable conditions along a single haul-route at any one point in time, challenges in monitoring haul

road condition and large trees on the side of the roads that cast shadows which of the potential to

confuse sensors and create unwanted collision obstacles should a truck veer off the narrow haul-road;

and

The automation of the extraction process is in the case of bauxite is more difficult. The variation of

impurities in bauxite ore is large and can occur at intervals as low as 0.5 metres in depth, requiring

selective mining which is challenging for current automation technologies.

At Alcoa, there is an organizational culture of continuous technical improvement that is implemented

worldwide through a partnership with Honeywell that is continuously exploring opportunities for automation,

but is yet to implement significant upstream automation at its Western Australian bauxite operations.


83

OTHER SECTORS

The shear diversity of operations that comprise other sectors of the resources industry render it very difficult

to even remotely generalize as to the issues these other sectors face when contemplating the implementation

of automated systems. In open pit and underground gold, precious metals, diamonds and base metals

operations the compelling case for investment in automation will depend on a wide range of factors that vary

considerably from operation to operations. These include:

Physical Scale

Generally speaking automation will be more compelling for large operations characterized by long

and deep haulage routes. However, physical scale does not appear to be adequately compelling in its

own right as other factors impact on the case for automation and this evidenced by the fact many

large gold, base metals and diamond underground and open pit operations that have investigated

automation and decided not to proceed.

Throughput

Generally speaking, automation will be more compelling for so called ‘fast moving’ mines that have

high volume throughput requiring the moving of significant amounts of material. This will mostly

apply to some of the larger, lower grade base metals operations.

Mine Life

Generally speaking, automation presents a more compelling case for operations with longer mine

lives, as this provides greater scope for pay-back on the investment and allows the capital to be

amortised over a longer period. This is a challenge to making the case for automation in many gold

operations, as they typically have relatively short projected mine lives at any one point in time due to

low resources to reserve conversion rates.

Nature of the Mining Operation

For mining operations that more resemble a high volume bulk commodity operation, automation is

likely to present a more compelling case as there is less of a requirement for precision and expert

judgment in tasks, rendering the automation process more simple, and as a result of scale, the

productivity improvements that can be realized through an automated system have a significant

impact on project returns. However, the case is less compelling, all things being equal, for mines that

revolve around selective mining processes.

Ratio of Mining Cost to Total Cost

In operations where the operating costs associated with mining is a relatively small portion of the

total costs of producing the commodity, investment in automation systems in the mining process will

generally be less compelling than in cases where the mining operation accounts for a high portion of

the total cost of producing the commodity.

Operational Layout

Many established operations have not been designed to optimally facilitate an extensive automation

system, and would face considerable switching costs in order to implement automation.

Type of Mining Process


84

Generally speaking, non-selective styles of mining lend themselves more easily to automation than

highly selective mining processes.

Degree of OH&S Risk that can be Mitigated by Automation

Operations that are characterized by higher than normal OH&S risk, as the result of factors such as an

unstable geotechnical environment or operations at altitude or in areas characterized by adverse

climatic conditions, will, generally speaking, be presented with a more compelling case to invest in

automation.


85

AUTOMATION AND WORKFORCE STRUCTURE

THE IMPACT OF AUTOMATION ON NEW SKILLS REQUIREMENTS, ORGANISATIONAL

CULTURE AND WORKFORCE STRUCTURE

As automation is progressively adopted by the resources industry, new technologies will be deployed that are

not supportable by the current resources industry workforce skill base, particularly in the case of the minerals

industry.

Furthermore, as discussed throughout this report, the culture of operations that adopt extensive automated

systems will change dramatically, again particularly in the case of the minerals industry. The new culture will

be based on a higher incidence of remote control, workforce diversity and integrated, multidisciplinary, data

rich problem solving. Additionally, the resources industry, for very good reasons, has a strong OH&S culture

embedded in work patterns. It is likely that as personnel are increasingly removed from hazardous operating

environments, as the result of automation, the safety culture will evolve into one that contains a stronger

element of systems reliability and systems redundancy modes of thinking about OH&S and other risks.

There is no doubt that automation will render certain roles in resources operations redundant as it has in

other industries. However, there is little evidence to suggest it will result in significant reduction in overall

employee numbers. Obvious candidates for redundancy are operators of the equipment that becomes

automated, such as drill rigs, loaders, haul trucks and trains. However, even in these obvious cases, some of

that workforce will most likely be retrained to operate equipment or sets of equipment remotely, and to

oversee components of the automated system. Some unskilled and semi-skilled roles may also be replaced by

automation.

The advent of automation is unlikely to result in a significant reduction of tradespersons that are employed on

a conventional resources operation, as most of the technical issues addressed by tradespersons will remain.

For example, while automated equipment may be designed for a higher incidence of ‘change-out’ style

maintenance where malfunctioning components are removed and sent off for repair and replaced by a spare

component on site, there is already a high incidence of this style of maintenance in modern resources industry

equipment. Routine mechanical issues such as oil leaks will still require maintenance attention on site.

Increased automation may indeed result in an increase in the number of electrical tradespersons required on

site to support change-outs and other ICT systems. However, different demands from tradespersons will most

likely be best addressed through modifications to trade qualifications and additional training. The removal of

driver error, may result in improved predictability of maintenance scheduling.

The change in skills, culture and workforce structure that results from automation will be felt most profoundly

in the minerals industry. As automation and remote control technology is increasingly adopted by the minerals

industry, its workforce will increasingly resemble that of the oil and gas industry workforce, with a smaller

portion of unskilled and semi-skilled labour and a larger portion of technicians and technical professionals

working in a process oriented culture.

While the precise impact of automation on workforce size and structure is not entirely clear, there is general

consensus among operators that the following three roles that are not usually associated with resources

industry, particularly mining operations, but are commonplace in other automated environments will become

increasingly important operational roles in the resources industry:


86

Automation Technician

Mechatronics Engineer

Operations Optimisation Manager

THE AUTOMATION TECHNICIAN

In 2009 the Kinetic Group (formerly the Mining Skills Centre) and the CRC Mining undertook a review of new

skills that might be required to support increased automation in the minerals industry. This work focused

primarily on the Vocational Education and Training (VET) sector, and the skills gap that needs to be addressed

to support automation. The new role of an automation technician was identified through this work.

The role of an automation technician is to build, install and maintain automated machinery and equipment. It

is largely a systems integration role, with electrical tradespersons still being required to perform functions such

as wiring, and mechanical tradespersons still required to address mechanical issues.

In the resources industry there are a number of stages required to commission a piece of equipment.

Traditionally, the equipment designer, an engineer, designs the equipment and a tradesperson is used to

install, repair and replace equipment. The gap that was identified by the Kinetic Group and CRC Mining is a

technical specialist that commissions and maintains the automated components of that equipment, the

Automation Technician. This role requires the Automation Technician to be competent across a broad range

of technologies and systems, to understand how these systems work together and to work with tradespersons

and engineers to effect installation and maintenance of that equipment.96

The Kinetic Group and CRC Mining identified the Certificate III Electrotechnology Electrician qualification

offered under the Electrotechnology Training Package as being the entry point qualification for an automation

technician. This was seen as a well-established pathway for entering the industry and preparing people for

working on electrical and electronic equipment in the mining environment. 97

Key areas of attention for a

reliable robotics system are operator interface, control room visualisation, high level robot allocation and task

scheduling, safe human-robot interaction and collision handling, motion planning, safety and reliability of the

SCADA control networks, camera viewpoint planning, 3D mapping, telerobotics, and system integration. 98

The work completed by the Kinetic Group and CRC Mining also highlights the alignment of the skill needs of an

automation technician to an electrical trade and instrumentation and control trade at a Certificate IV level.

However, the work also notes that a qualification pathway limited only to the electrical trades limits the

background of others who may well suit the role of Automation Technician such as mechanical fitters and

automotive mechanics.99

The Kinetic Group and CRC Mining undertook considerable analysis to determine the specific skills that would

be required by an Automation Technician in the resources industry. Details of the specific tasks that are likely

to be required of the automation technician, either independently or with the support of tradesperson or

engineer are listed in Appendix 1. The analysis also discusses communication, problem solving, planning and

96




Mining Industry Skills Centre, Automation Skills Strategy Formation


87

organization skills that will be required by a resources industry automation technician.100

Table 9 below

summarises the overall skill and expertise set that will be required by an resources industry automation

technician.

Skills Knowledge

ROLE SKILLS Communication Interpreting drawings and diagrams

Standards/regulation compliance Interpreting catalogues and manuals Problem reporting and documentation

Regulations and standards Drawing conventions

Problem Solving Fault finding Problem analysis and correction Database diagnosis Hazard identification

Hazard types Fundamental statistics

Planning and Organisation Costing and purchasing Quality assurance Maintenance planning Risk management Field experimentation

Basic mining operations Safe working practices Safety regulations Environmental regulations

TECHNOLOGIES Control Technologies Control circuit interpretation

PLC programming Embedding PC programming

Control device types Control system principles

Communications and Computer Technologies

Computer configuration Network installation

Current loops Fieldbus technology Computer networking principles Wireless digital communication Operating system types

Electrical Applications and Apparatus Installation and repair Rotating machines Electrical Installations and Systems Wiring

Arrangement Equipment selection System verification

Wiring system types Installation regulations

Electrical Principles Fundamental electrics DC principles AC principles Electromagnetic principles

Electronic Principles and Applications Digital/analogue signal processing Electronic components type Digital electronic principles

Equipment and Tools Tool use and care Dismantling and assembling

Tool types

Instrumentation Installation and calibration Position sensors Velocity sensors Navigation sensors Range sensors Mechanical sensors

Table 9 - Current Skills Requirements of an Automation Technician

If deployed in an operating environment today, it is expected that an Automation Technician would be heavily

reliant on support or direction from other experts (engineers and tradespersons) to perform many of the tasks

summarised in Table 9. This is illustrated in Figure 17 below.101

100


Adapted from: Mining Industry Skills Centre, Automation Skills Strategy Formation


88

Figure 17- Support Required by the Automation Technician Role Today

However, as automation becomes more prevalent on operational sites, it is expected that operators will

require a greater level of skill from Automation Technicians, with the position requiring the application of

knowledge and skills across a far wider range of roles and technologies independently, and that VET programs

and companies will respond to this need by adequately modifying qualifications, and on the job training.

Indeed the only skill that should require expert direction within five years is embedded PC programming.

Within 15 years the automation technician should be able to meet all skill and knowledge requirements either

independently or with the support of other experts. This is illustrated in Figure 18 below.

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Level of Support Required by Automation Technician Today Across Various Tasks Today

perform under direction of experts

Perform with support from other experts

Perform independently


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Figure 18 - Support Required by the Automation Technician Role within 15 Years

It is expected that the only skills and knowledge that the automation technician will require support within 15

years time are:

Control Technologies:

o PLC Programming

o Embedded PC Programming

o Control Parameter Selection

Communications and Computer Technologies:

o Computer configuration

o Fieldbus technology

o Computer networking principles

o Wireless digital communication

o Operating system types

Electrical Installations and Systems

o Equipment selection

o System verification

The fact that the Automation Technician will be required to work within a multidisciplinary, trade and

professional team implies the role will require well developed soft skills across communications, planning and

organization, problem solving and self management. The required soft skills are summarised in Table 10

below.102

102

Mining Industry Skills Centre, Automation Technician Soft Skills

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Level of Support Required by Automation Technician Across Various Tasks in 15 Years

Perform with support from other experts

Perform independently


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Soft Skill Area Specific Soft Skills

Communications - Ability to communicate with a range of stakeholders – operators, trades, engineers, vendors and management

- Reading and interpreting documentation – product manuals and schematics

- Report writing and feedback – sound literacy and numeracy, computer literacy and presentation skills – both oral and written

Planning and Organisation - Risk management and change management (analysing changes, identifying risks and consequences of actions)

- Ability to prioritise tasks and manage time and resources – management plan creation

- Situational awareness – production demands, financial impacts and drivers

Problem Solving - Root cause analysis

- Ability to work independently - Capable of handling pressure and decision making - Understanding limitations and seeks assistance - Ability to think visually - Structured process for fault finding - Ability to utilise available resources and consider alternative

options to resolve a problem

Self Management - Taking responsibility for personal performance - Can do attitude, commitment and drive - Fit for work and attendance

Table 10 – Automation Technician Soft Skill Requirements

MECHATRONICS ENGINEER

Mechatronics engineering is a multidisciplinary field that combines electrical, mechanical, computing and

software engineering to create expertise in designing, building, deploying and maintaining electromechancial

devices such as robotics. As discussed in the first section of this report, mechatronic technologies are central

to field robotics, and the application of automated and remote control systems to resources industry

operations.

A particular skill set that is common to mechatronics engineers that is crucial to many resources operations

automation programs is data fusion expertise. Because highly automated resources industry operations

produce enormous volumes of data from heterogeneous data streams, the ability to write software code that

can interpret and integrate those heterogeneous data streams is critical to the operation of automated

systems and optimizing their benefits.

Engineers on conventional resources industry operations typically come from mining, petroleum, mechanical,

civil and electrical engineering backgrounds. Few students of mechatronics engineering programs undertake

the program with a view to a career in the resources industry. As such, the mechatronics engineers are

currently highly reliant on conventional resources industry engineers in understanding how to effectively

deploy automated devices in a resources operation environment.


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PRODUCTION MANAGERS AND PROCESS OPTIMISATION EXPERTS

As resources operations become more automated and the immediate benefits of the automation program

have been realized, significant additional benefits can be attained through optimization, as has been the

experience of other largely manual processes that have achieved high levels of automation. This role applies

expertise in logistics and process optimization to achieve optimal whole of operations productivity and other

benefits.

The objectives of the role are typically to reduce variation in process performance and product quality,

minimize costs, minimize downtime and optimize scheduling. While some formal training is available in this

area, experts in this field frequently acquire skills though roles in manufacturing, logistics or the military.

In a highly automated resources operation the opportunity for operations optimization is large by virtue of the

significant amount of data that is available to make optimization decisions.

THE MARKET FOR NEW RESOURCES INDUSTRY AUTOMATION ROLES

The Kinetic Group also estimated that based on the assumption that 50 percent of the 500 resources industry

sites required 3 to 5 automation technicians, 1,500 such roles would need to be filled over the next decade. In

light of the discussion in this paper on the complexities associated with the adoption of automation in the

resource industry, it is unlikely that demand for automation technicians will emerge to this extent in the short

term. Anecdotally, it would seem that the functions of an automation technician are currently being filled by

resources companies implementing automation from two key sources:

Electrical tradespersons who acquire the additional skills required to perform the Automation

Technician role through experience and some on-the-job training. It was noted from the interviews

associated with this report that this pathway will not be adequate in the longer-term because many

trade staff will struggle to attain the higher-level skills that are required for the job; and

Technicians operating in other industries that have higher-level automation related skills. In the

mining industry a significant portion of such technicians seem to be recruited from the armed forces

and in the case of the oil and gas industry, from the Navy’s Submarine Service specifically.

Most leading universities in Australia offer programs in mechatronics engineering (see next section) and many

manufacturing industries across Australia employ mechatronics engineers. However, there is anecdotal

evidence that educating mechatronics engineers in resources industry operations can be problematic103

. Some

operations report that electrical engineers with resources industry experience can quickly develop the

expertise relevant to the deployment and maintenance of some automated equipment.

In the shorter term production optimization managers will most likely be sourced from logistics intensive

industries such as transport, manufacturing and the military and presumably candidates recruited from these

industries will require some training to acquire and adequate understanding of the particular resources

industry operation. In the longer-term it is likely that the industry would benefit from a post graduate program

in resources industry operations optimization (see next section).

103

Business-Higher Education Round Table (2011), ICT, Technology, Skills – The Changing Face of Mine Operations and Management, Position Paper Number 15


92

As the minerals industry progresses toward a more highly automated environment, its workforce needs in

terms of skills and experience will more closely emulate that of the oil and gas industry. This may place

pressure on the oil and gas industry with respect to loss of workers to the minerals industry and pressure on

both industries as they compete for similar workers.


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IMPLICATIONS FOR VOCATIONAL EDUCATION AND TRAINING

As the Automation Technician role becomes more commonplace in the resources industry, there will most

likely be a requirement for the VET sector to develop a training program that delivers a qualification that

certifies that an individual has the appropriate skills to perform that role. There seems to be general consensus

among Registered Training Organisations (RTOs), institutions of higher education and industry that current

curricula does not currently provide for a comprehensive set of automation technician skills within a single

existing qualification, but that the required material to develop a new qualification generally exists. While VET

programs will inevitably need to evolve to provide this qualification, the analysis in this report, suggests that

the need is not as urgent as previously assumed.

The current absence of a resources automation technician qualification is primarily the function of the

following two factors:

Absence of an immediate market

The development and delivery of courses by training and education organizations is a function of the

immediate market for those courses. It is likely that there is currently not a significant enough

employment market for graduates with a comprehensive set of skills in resources industry

automation, and therefore limited student demand. This is a function of the fact that extensive

automation is not currently widely adopted, and that where extensive automation is adopted, skills

and expertise gaps are being filled by electrical engineers, or engineers and tradespeople with

automation skills that have been developed in other industries such as defense. It is unlikely that

institutions will invest in resources industry automation programs to any great extent until there is an

adequate addressable market for the courses.

Commercial-in-Confidence nature of many automation programs

Most of the extensive automation programs that are currently being developed and deployed are

being done so by large multinational mining companies who are seeking first mover advantage in

automation. As such, the intellectual property associated with these programs is being treated as

commercial-in-confidence. The training of deployment and maintenance staff for these programs is

typically being conducted in collaboration with an equipment OEM or under an exclusive

arrangement with a specific institution of training and/or education. This makes it difficult for other

institutions to develop and validate general resources industry automation curricula.

VOCATIONAL EDUCATION AND TRAINING PROGRAMS

At a mechanical trade qualification level (Certificate III), it is possible to cover some basic electrical concepts

and to obtain a restricted electrical license. However, this is significantly deficient with respect to the skills

required of an automation electrician as discussed in a previous section of this report. An electrical trade

qualification covers the required electrical skills more comprehensively including control technologies such as

PLC, but still falls short of the required skill set. While a dual trade qualification (mechanical and electrical)

would substantially progress a tradesperson toward the required qualified skill set, it will also still be deficient.

It is therefore not surprising that both public and private RTOs are trending toward creating a qualification for

an automation technician as a post trade qualification, typically at Diploma level, but in some cases associate

degrees (see Charles Darwin University and Central Queensland University below). There is also a view that


94

most of the material for this post-trade qualification could be compiled by combining content from a range of

existing electrical and mechanical Certificate IV and Diploma qualification curricula.

The following subsections cover a selection of public and private RTO’s that deliver programs whose content is

relevant to creating a post trade program for automation technicians.

CENTRAL TAFE – DIPLOMA IN ENGINEERING – TECHNICAL (MECHATRONIC)

Central TAFE in Perth, Western Australia currently offers a diploma level program in mechatronics. This

program was developed in conjunction with the manufacturing industry and focuses primarily on the

application of mechatronics to manufacturing. The minimum entry requirements for this program are

Certificate III in Mechanical Engineering or:

Well developed communications skills, which translates to at least a B grade in Year 10 English, A

grade in English Stage 1 or C grade in English Stage 2; and

Well developed mathematics skills, which translates to at least a B grade in Year 10 mathematics, A

grade in mathematics Stage 1 or C grade in mathematics Stage 2.

Entry into the Certificate III in Mechanical Engineering program requires:

Developed communications skills, which translates to at least a C grade in Year 10 English, a C/B grade

in English Stage 1, or a D grade in English Stage 2; and

Developed mathematics skills, which translates to a C grade in Year 10 Mathematics or a D grade in

Mathematics Stage 1.

The program for the Certificate III in Mechanical Engineering is summarised in Figure 19 below.104

104

Central TAFE


95

Figure 19 - Certificate III Engineering - Technical Program - Central TAFE

Figure 20 below summarises the structure of the Diploma in Engineering – Technical (Mechatronics).105

105

Central TAFE

Office Practice Cluster

Drafting Cluster

Communication Cluster

1. Organise and communicate information2. Interact with computer technology3. Participate in environmentally sustainable work

practices4. Perform computations

1. Produce basic engineering graphics2. Use CAD to create and display 3D models3. Use CAD systems to produce basic engineering

drawings4. Read and interpret plans and specifications

1. Use hand tools2. Contribute to the development of products and

processes

Certificate III in Engineering - Technical


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Figure 20 - Diploma in Engineering – Technical (Mechatronics)

The model of developing an automation technician program in conjunction with industry will be critical in

meeting the resources industry’s specific automation technician skill needs. Furthermore, there may well be

generic course material that can be adapted from the program summarised in Figure 20 above.

CHALLENGER TAFE – AUSTRALIAN CENTRE FOR ENERGY AND PROCESS TRAINING

Challenger TAFE is a VET institute with over 23,000 students each year undertaking full and part-time study

across a diverse range of subjects at 17 locations in the Perth metropolitan and Peel region. Challenger TAFE is

the owner and operator of the Australian Centre for Energy and Process Training (ACEPT), a Western

Australian Government, Federal Government and industry funded facility designed to deliver VET qualifications

to oil and gas industry plant operators. The facility has considerable real-world and simulation based training

assets including a fully operational closed loop process train and associated remote operations room that is

used to train process operators and industrial instrumentation technicians. The closed loop process train

includes:

Electrical Cluster

CAD Cluster

Communication Cluster

Materials Cluster

Core

1. Apply basic electro & control scientific principles &techniques in mechanical and manufacturing engineeringsituations

2. Select & test components for simple electronic switching & timing circuits

3. Analyse a simple electrical system circuit

1. Use CAD systems to produce basic engineeringdrawings

2. Produce basic engineering graphics3. Use CAD to create & display 3D models

1. Interact with computing technology2. Organise & communicate information

1. Select & test mechanical engineering materials2. Select common engineering materials

1. Apply mathematic techniques in manufacturing,engineering & related situations

Circuits

Automation Cluster

Manufacturing Cluster

Mechanical Cluster

Core

1. Solve problems in electromagnetic circuits

1. Apply mechatronic engineering fundamentals to the support, design & development of projects

2. Operate & program computers & controllers inengineering situations

3. Set up basic pneumatic circuits

1. Perform mechanical and fabrication drafting2. Manufacture or modify plant, tooling, equipment or

systems

1. Contribute to design of basic mechanical systems2. Apply basic scientific principles & techniques in

mechanical engineering situations

1. Participate in environmentally sustainable workpractices

Stage 1 Stage 2

Diploma in Engineering – Technical (Mechatronics)


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An instrument air unit;

Separation units that separate nitrogen from air and oil from water;

A tank farm for storage of process chemicals;

Chemical recycling unit;

A fully operational closed loop methanol distillation tower

Honeywell process control system;

A full-scale Honeywell process train simulation module

A Yokogawa distillation tower, instrument air, furnaces, heat exchangers, chemical reactor and gas

compressors simulation

ACEPT offers a range of VET qualifications under the PMA08 Chemical, Hydrocarbons and Oil Refining and/or

MEMO5 Metals and Engineering Package. These qualifications are summarised in Table 11 below.106

106

http://www.challenger.wa.edu.au/Workingwithindustry/AustralianCentreforEnergyandProcessTraining/Pages/AbouttheCentre.aspx


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Cert III in Process Plant Operations

Cert IV in Process Plant Operations

Diploma of Process Plant Technology

Advanced Diploma of Process Plant

Technology

Entry Requirement Year 12 with passes in Mathematics; or Cert II in Process Plant Operations

Cert III in Process Plant Operations

Cert IV in Process Plant Operations

Diploma of Process Plant Technology

Duration 6 months 6 months 6 months 6 months Mandatory Units Following emergency

response procedures Applying workplace procedures Communicating in the workplace Participating in environmentally sustainable work practices Work safety

Following emergency response procedures Applying workplace procedures Communicating in the workplace Participating in environmentally sustainable work practices Work safety

Participate in environmentally sustainable work practices Achieve work outcomes Process and record information Work safely

Participate in environmentally sustainable work practices Achieve work outcomes Process and record information Work safely

Elective Units Operate a production unit Produce product by distillation Operate reactors and reaction equipment Operate and monitor compressor systems and equipment Operate process control equipment Undertake ship loading/unloading Conduct artificial lift Undertake well management Produce product using gas absorption Produce product using fixed bed hydration Conduct pipeline pigging Operate cryogenic processes Operate a gas turbine Operate and monitor a steam turbine Operate and monitor a steam turbine Shutdown and isolate machines/equipment Issue work permits Provide training through instruction and demonstration of work skills

Optimise process/plant area Monitor remote production facilities Manage plant shutdown and restart Lead team culture Ensure process improvements are sustained Improve cost factors in work practices Contribute to workplace OHS management skills Assess risk Coordinate maintenance Coordinate permit process Coordinate Incident report Development plant documentation Commission/recommission plant Decommission plant Participate in HAZOPS studies Plan and organize assessment Assess competence

Provide operational expertise to a project team Control the processes in abnormal situations Determine energy transfer loads Manage utilities Plan plant shutdowns Coordinate plant shutdowns Facilitate work team Manage operational plan Maintain the workplace OHS management system Manage risk Contribute to a safety case Manage emergency incidents Establish incidence response preparedness and systems Optimise production system Analyse equipment performance

Modify plant De-bottleneck plant Manage people relationships Manage workplace learning Establish a workplace OHS system Build partnerships to improve incidence response Manage diversity Management environmental management systems Manage change Manage a crisis Maintain a quality system and continuous improvement Process within a work or functional area Manage 5S system in a manufacturing environment Implement a continuous improvement system

Table 11- Australian Centre for Energy and Process Training Process Operations Programs


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In addition to offering these qualifications to people interested in a career in the oil and gas industry, ACEPT

works closely with operators to help evaluate workforce capability, identify skill needs, develop career

pathways and design and deliver training.

While the programs summarised in Table 11 are targeted at technicians and operators working on oil and gas

process trains, and the training facilities themselves revolve around oil and gas processes, the model of a

simulated remote operations centre is highly relevant to at least a component of skills required by an

automation technician

A facility designed for mining automation technicians could potentially leverage from the facilities at ACEPT.

Indeed ACEPT is currently working with the Rio Tinto ROC team to train operators with field experience to

perform roles within the ROC.

CHARLES DARWIN UNIVERISTY

Charles Darwin University is located in Darwin, Northern Territory and delivers both higher education and VET

programs. In 2010, Charles Darwin University, delivered courses to over 14,000 students across 200 VET

qualifications included non-accredited courses, Certificate I,II, III and IV, diplomas and advanced diplomas. It

also offers an associated degree in process engineering, bachelor of engineering, bachelor of information

technology, masters of engineering and masters of information technology (software engineering). Charles

Darwin University is also offering a certificate course in process operations that is delivered in conjunction with

Challenger TAFE’s Australian Centre for Energy and Process Training.

Much of this activity is supported by the $6.0 million North Australian Centre for Oil and Gas, which is located

at Charles Darwin University. While focused on developing skills for the oil and gas industry, elements of the

structure of VET programs at Charles Darwin University is of interest to developing a program for automation

technician. In particular:

All students are required undertake a compulsory unit in cultural intelligence and capability and a

compulsory units in communicating technology. These units could be adapted to support the

development of soft skills that will be required by an automation technician as discussed in a previous

section of this report; and

The flexibility afforded by having the option to choose elective units from a range of 100 units offered

by the university as part of the VET program, provides scope to tailor student training to the needs of

a particular sector or operation.

Examples of the general structure of VET programs offered by Charles Darwin University are provided in the

form of the Diploma of Engineering and Associated Degree in Process Engineering as summarised in Table 12

below.107

107

http://stapps.cdu.edu.au/pls/apex/f?p=100:31:421417842176868::NO::P31_SEARCH_COURSE,P31_SEARCH_YEAR,P31_SEARCH_VERSION,P31_TAB_LABEL:DIPEN,2012,4, AND http://stapps.cdu.edu.au/pls/apex/f?p=100:31:421417842176868::NO::P31_TAB_LABEL:Course%20Structure

http://stapps.cdu.edu.au/pls/apex/f?p=100:31:421417842176868::NO::P31_SEARCH_COURSE,P31_SEARCH_YEAR,P31_SEARCH_VERSION,P31_TAB_LABEL:DIPEN,2012,4

http://stapps.cdu.edu.au/pls/apex/f?p=100:31:421417842176868::NO::P31_SEARCH_COURSE,P31_SEARCH_YEAR,P31_SEARCH_VERSION,P31_TAB_LABEL:DIPEN,2012,4

http://stapps.cdu.edu.au/pls/apex/f?p=100:31:421417842176868::NO::P31_TAB_LABEL:Course%20Structure


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Diploma of Engineering Associate Degree in Process Engineering

Common Units Cultural Intelligence and Capability Design and Innovation: Communicating Technology

Cultural Intelligence and Capability Design and Innovation: Communicating Technology

Core Units Statistics Electrical Engineering Introduction to Mathematics Concepts of Physics

Concepts of Chemical Engineering Statistics Engineering Foundations Electrical Engineering and Computing Chemical Concepts Organic and Inorganic Chemistry Introduction to Mathematics Mathematics 1A Concepts in Physics Process Analysis Fluid and Thermodynamics Project Management Industrial Experience

Electives Two units selected from 100 units offered by the University

Two units selected from 100 units offered by the University

Table 12 – Example of VET Course Structure at Charles Darwin University – Diploma of Engineering and Associated Degree in Process

Engineering

CENTRAL QUEENSLAND UNIVERSITY

Central Queensland University has six campuses in regional Queensland, as well as a campus in Brisbane, Gold

Coast, Melbourne and Sydney. The University offers a range of associated degree programs that are designed

to train paraprofessionals that can support engineers, geoscientists and other professionals on resources,

primarily mining, operations. While associate degree qualifications are probably above what is required to

adequately skill an automation technician in most operating environments, the following associate degrees are

of interest to this analysis:108

Associate Degree of Engineering

This associated degree aims to develop skills in applications and interactions within systems, and

combine sound engineering understanding with modern technology.

Associate Degree of Mine Technology

This associated degree is aimed at educating the technical workforce at the engineering associate

level to meet the needs of mining, engineering and mineral processing for the mining industry.

Associate Degree of Mine Operations Management

This associate degree provides the generic and technical mine operations management knowledge

and skills to prepare students to meet the targets and responsibilities of mine operations. It

incorporates engineering management, safety and science courses.

108

http://www.cqu.edu.au/study/what-can-i-study/engineering,-mining-and-technology/undergraduate

http://www.cqu.edu.au/study/what-can-i-study/engineering,-mining-and-technology/undergraduate


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Each associate degree is delivered entirely through distance education on a four-year part-time basis, with

much of the learning activity focused on conducting practical exercises on site. This mode of delivery means

that an associate degree in engineering or an associate degree in mine technology, or indeed a subset of the

units in each, could be used to up-skill trade qualified staff for the position of automation technician, without

entirely losing the productivity of those staff during the training period. Additionally, the associate degree in

mine operations management could potentially be used to up-skill automation technicians recruited from

other industries on issues associated with minerals operations.

WESTRAC INSTITUTE

A number of resources companies and OEMs are RTOs in their own right, delivering internal training programs

with nationally accredited qualifications.

An example of a private RTO is the Westrac Institute. Westrac is one of the world’s largest dealers of

Caterpillar heavy machinery, supplying equipment to the building and heavy construction, forestry, local

government, marine, highway truck, quarry and aggregates and mining industries across Australia and

Northern China. Founded in Western Australia, WesTrac now has over 4,500 employees operating across 102

branches in Australia and China, including 1,750 trades people and technical assistants.

Caterpillar equipment is regarded as a market leader in many sectors of the global mining equipment and

technology market including large mining trucks, dump trucks, wheel loaders, motor graders, scrapers and

track-type tractors. A large proportion of WesTrac’s business revolves around the mining industry market,

especially in Western Australia where WesTrac is a key supplier of equipment and technology to the

industry.109

Caterpillar and Westrac are working with a number Australian mining companies and operations

on automation programs, including BHP Billiton and Fortescue Metals Group.

The WesTrac Institute in Western Australia is located at the company’s headquarters in South Guildford and

was established as a Registered Training Organisation in 1985. The WesTrac Institute provides employees and

customers of WesTrac with opportunities in pre-trade and post-trade training, training in machine operations,

Occupational Health and Safety (OH&S) and management training. There are currently approximately 530

apprentices completing apprenticeships with the support of the WesTrac Institute, including 140 apprentices

that are employees of customers of WesTrac like Downer EDI, MacMahons, BHP Billiton, Newmont, Barrick

Gold and Alcoa. These apprentices are completing qualifications up to Certificate IV in auto-electrical,

boilermaker, high voltage electrical, machine operations and plant mechanic trades. A number of WesTrac’s

apprentices are from Indigenous backgrounds.110

The Westrac Institute offers the following courses up to Certificate III:

Heavy Vehicle Mechanics (Mobile Equipment)

Heavy Vehicle Mechanics (Road Transport)

Automotive Electrician

Power Generation Electrcians

Boiler Maker Welders

1st

Class Machinists

109

Chamber of Minerals and Energy Western Australia (2012), Resources Industry Training Case Studies 110

Chamber of Minerals and Energy Western Australia (2012), Resources Industry Training Case Studies


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The Westrac Institute also offers post-trade qualifications that are specific to Caterpillar equipment. While

general automation technician skills are not covered comprehensively as yet, under the autonomous truck

development plan with Fortescue Metals Group, Westrac will be developing an operations and maintenance

training program. Instructors at the Westrac Institute will be trained on how to deliver this program. It is likely

that automation skills will be delivered at a post-trade qualification level at the Westrac Institute.


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IMPLICATIONS FOR HIGHER EDUCATION

The implications of the emergence of an increasing incidence of automation for undergraduate engineering

qualifications are as yet clear. On the face of it, universities, particularly the universities with robust, multi-

disciplinary engineering schools should have adequate capability to be quite flexible in course offerings such

that the professional engineering needs of a more automated resources industry can be met, albeit substantial

course changes in engineering will be required to navigate the accreditation processes of the individual

institution’s academic council as well as that of Engineers Australia.

Some institutions report that mechatronic engineers are highly sought after by, particularly, the mining

industry primarily as a result of their somewhat unique expertise in data fusion that is required for the

assembly, interrogation and analysis of heterogeneous data sets and streams that are inherent to automated

mining systems. Whereas other institutions report that the resources industry finds it difficult to understand

where a pure mechatronics engineering degree fits, as graduates are typically relatively deficient in important

areas of mechanical and electrical engineering and in mining and oil and gas processes. Furthermore, many

resources companies are currently filling the competency gap created by increased automation by deploying

conventionally qualified electrical engineers who seem to attain most of the necessary additional skills through

experience with the technology.

Generally speaking, it would seem that two different pathways are possible for the training of engineers with

adequate skills and expertise to work with more automated resources industry systems:

Mechatronics Engineering in Resources Undergraduate Degree

It would seem that the main challenge resource companies face in employing a mechatronics

engineering graduate is the lack of expertise in mining or hydrocarbon production processes

possessed by the graduate, as conventional mechanical and electrical engineering can be harnessed

by employing mechanical or electrical engineers. As such, there is a possibility that a specialised

mechatronics engineering in resources undergraduate degree may emerge. This is unlikely to

eventuate until the adoption of automation is so adequately comprehensive that a specific new

resources industry technical profession in automation emerges.

Post Graduate Qualification

In the short to medium term, it is more likely that a post-graduate qualification such as a graduate

diploma or masters degree in mechatronic engineering that is focused on developing the required

automation expertise in mechanical, electrical, mining or oil and gas engineering graduates, will be

the most practical pathway for relevant formal qualifications.

The high incidence of commercial confidentiality that surrounds proprietary automation programs is making it

difficult for universities to assess future skill needs and determine capability that needs to be built into

faculties for the delivery of future programs. While some industry automation programs are working directly

with specific universities and other training organizations to develop packages for their employees, it is

unlikely that wider consultation will occur until automation becomes more ubiquitous.


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CURRENT UNIVERSITY ENGINEERING PROGRAMS

The following subsections provide an analysis of the curriculums in mechanical engineering, electrical

engineering, mechatronics engineering, mining engineering and petroleum engineering at Australian

universities that offer mining and petroleum engineering undergraduate courses, namely:

University of Western Australia

Curtin University

University of Queensland

University of New South Wales

While the University of Sydney does not offer programs in mining or petroleum engineering, its program in

mechatronics is also examined for the purposes of this study because of its pedigree and association with the

Australian Centre for Field Robotics which has undertaken considerable research and development in the

application of field robotics to the Australian resources industry (see previous section of this report).

This analysis highlights the following:

Within the combined curricula at each institution there appears to be a plethora of course material,

that subject to the requirements of the specific institution’s academic council and Engineers Australia,

could potentially be reconfigured to at least form the basis of formal qualifications at either an

undergraduate or graduate level to meet the foreseeable technical professional needs of the

resources industry as demand dictates;

In all cases, the electrical and electronic engineering curricula most closely resembles that of the

mechatronics curricula, noting that in some cases, a limited number of subjects more typically taught

as part of a mechatronics or electrical engineering degree are also taught in the mechanical

engineering degree; and

In all cases, the content in the mining engineering and petroleum engineering curricula is the most

removed from the mechatronics degree curricula.

This implies that electrical engineers are more likely to have more of the expertise required to work with

automated systems than other non-mechatronics engineering graduates and that mining and petroleum

engineering graduates are likely to have the least appropriate technical background, other than their

understanding of resources processes. However, dual-undergraduate qualifications or an appropriate post-

graduate qualification could be developed to deliver the required complete set of expertise.

UNIVERSITY OF WESTERN AUSTRALIA

The University of Western Australia (UWA) has recently transformed its undergraduate teaching model to a

‘3+2’ course structure, which means in the case of professional undergraduate degrees such as engineering

students complete a generalized bachelor’s degree and a specialised master degree in order to receive their

formal qualification. This structure seems highly suitable to delivering an optimal mix of qualifications for a

professional resources automation engineer. Table 13 below compares the UWA mechanical engineering,

electrical and electronic engineering and mechantronics engineering course content.111

111

www.studyat.uwa.edu.au/courses/engineering-science


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Units Mechanical Engineering Electrical and Electronic Engineering Mechatronics Engineering

Level 1 Core Material Behaviour from Atoms to Bridges Engineering Dynamics

Digital Systems Power and Machine Technologies

Object-oriented Programming and Software Engineering Programming and Systems Digital Systems 1 Engineering Dynamics

Level 2 Core Modeling and Computer Analysis for Engineers Engineering Mathematics Engineering Design and Visual Communications Manufacturing Petroleum Engineering Fundamentals (Oil & Gas Major)

Circuits and Electronic Systems 2 Digital System Design Embedded Systems Physical Electronics 2 Fundamentals of Electrical Engineering Modeling and Computer Analysis for Engineers Engineering Mathematics

Circuits and Electronic Systems 2 Digital Systems Design Electromagnetics and Electromechanics Embedded Systems Engineering Mathematics Engineering Design and Visual Communication Manufacturing

Level 3 Core Fluid Mechanics Solid Mechanics Control and Mechatronics Thermofluids 3 Mechanical Design Vibration and Signal Processing Structural Integrity Mechanisms and Multibody Systems Mass and Energy Balances (Oil & Gas Major) Unit Operations and Unit Processes (Oil and Gas Major) Introduction to Offshore Engineering (Oil and Gas Major) Reservoir Engineering (Oil and Gas Major)

Signals and Systems Circuits and Electronic Systems Electromagnetic Theory Signals and Systems 3 Engineering Management and Industrial Practice

Mechatronics Design Control and Mechatronics Vibration and Signal Processing Mechanisms and Multibody Systems

Level 4 Core Engineering Tribiology and Maintenance

Electrical and Electronic Engineering Project Part 1 Electrical and Electronic Engineering Project Part 2

Mechatronics Engineering Project Part 1 Mechatronics Engineering Project Part 2 Advanced Control Engineering

Project A Mechanical Engineering Project Part 1 Mechanical Engineering Project Part 2

Project B Oil and Gas Engineering Project Part 1 Oil and Gas Engineering Project Part 2

Group A Option

Project Engineering Practices Engineering for Sustainability

Group B Option

Reliability Engineering Mass and Energy Balances Extractive Metallurgy-Principles Extractive Metallurgy – Practice Unit Operations and Unit Proceses Process Modeling Advanced Prediction of Fluid Properties Process Systems 2 Object-oriented Programming and Software Engineering Computer Analysis and Visualisation Hydraulics II Introduction to Offshore Systems Petroleum Systems Heat and Mass Transfer Process Synthesis and Design

Electric Machines Analogue Electronics


106

Units Mechanical Engineering Electrical and Electronic Engineering Mechatronics Engineering

Introduction to Micro-electromechanical Systems Materials Engineering 2 Materials Engineering 3 Non-metallic Materials Engineering Project 1 Engineering Project 2 Acoustical Engineering Design Tools: Finite Element Modeling Computational and Experimental Fluid Dynamics Thermofuilds 4 Fundamentals of Engineering Fabrication and Metalworking Processes Advanced Control Engineering Introduction to Chemical and Resource Engineering Offshore Design Project History, Economics and Geopolitics of Oil and Gas Petroleum Engineering Fundamentals Drilling and Completion Engineering Reservoir Engineering Reservoir Characterisation Production Optimisation Reservoir Simulation Reservoir and Well Performance

Group C Option

Units chosen from across the University with permission of the faculty

Process Instrumentation and Control

Group D Option

Control Engineering Digital Communications and Networking Digital Microelectronics Systems Design Power Transmission and Control

Table 13 - University of Western Australia - Mechanical, Electrical and Electronics and Mechantronics Engineering Course Content

Table 14 below compares the UWA mining, petroleum and mechatronics engineering degree course

content.112

112

www.studyat.uwa.edu.au/courses/engineering-science


107

Units Mining Engineering Petroleum Engineering Mechatronics Engineering

Level 1 Core Object-oriented Programming and Software Engineering Material Behaviour from Atoms to Bridges Introduction to Chemical and Resource Engineering

Object-oriented Programming and Software Engineering Programming and Systems Digital Systems 1 Engineering Dynamics

Level 2 Core Engineering Geology and Mechanics Geomechanics Surveying and CAD Engineering Mathematics

Modeling and Computer Analysis for Engineers Engineering Mathematics History, Economics and Geopolitics of Oil and Gas Petroleum Engineering Fundamentals

Circuits and Electronic Systems 2 Digital Systems Design Electromagnetics and Electromechanics Embedded Systems Engineering Mathematics Engineering Design and Visual Communication Manufacturing

Level 3 Core Project Management and Risk Engineering Mineral Resources Fluid Mechanics Solid Mechanics Rock Mechanics Surface Mining Underground Mining

Petroleum Systems Fluid Mechanics Solid Mechanics Mass and Energy Balances Thermofluids Drilling and Completion Engineering Reservoir Engineering Reservoir Characterisation

Mechatronics Design Control and Mechatronics Vibration and Signal Processing Mechanisms and Multibody Systems

Level 4 Core Reliability Engineering Geotechnical and Geoenvironmental Engineering Mining Engineering Project Part 1 Mining Engineering Project Part 2 Mine Design Underground Mining 2 Mining Management Geotechnology of Mine Waste Management

Engineering for Sustainable Development Oil and Gas Engineering Project Part 1 Oil and Gas Engineering Project Part 2 Production Optimisation Reservoir Simulation Reservoir and Well Performance

Mechatronics Engineering Project Part 1 Mechatronics Engineering Project Part 2 Advanced Control Engineering

Table 14 - University of Western Australia - Mining, Petroleum and Mechatronics Engineering Course Content

CURTIN UNIVERSITY

Table 15 below compares the Curtin University mechanical, electronic and communication and mechatronics

engineering course content.113

Units Mechanical Engineering Electronic and Communication Engineering

Mechatronics Engineering

Core Automatic Control Dynamic Systems Electrical Plant Engineering Graphics Engineering Law Engineering Management Engineering Mathematics

Advanced Digital Design Communications Engineering Communications Signal Processing Control Systems Data Communications and Networking Digital Signal Processing

Automatic Control Electrical Circuits Embedded Systems Engineering Engineering Graphics Engineering Law Engineering Management Engineering Mathematics

113

http://engineering.curtin.edu.au/courses/ug_courses.cfm


108

Units Mechanical Engineering Electronic and Communication Engineering

Mechatronics Engineering

Engineering Sustainable Development Fluid Flow Modeling Fluid Mechanics Industrial Technology Machine Dynamics Manufacturing Processes Materials Mechanical Design Mechanical Project Professional Practice Strength of Materials Thermal Engineering Processes Thermodynamics

Electrical Circuits Electromagnetic and Electromechanical Energy Conversion Electronic Design Electronic Fundamentals Engineering Electromagnetics Engineering Management Engineering Programming Engineering Project Foundations of Digital Design Legal Framework and Sustainability in Electrical Engineering Mathematics Microcomputers Mobile Radio Communications Signal and Systems

Engineering Sustainable Development Foundations of Digital Design Linear Systems Modeling Machine Dynamics Manufacturing for Mechatronics Mechanical Design Mechatronic Automation Mechatronic Modeling Mechatronic Project Mechatronic Systems Design Power Electronics Professional Practice Unix and C Programming

Optional Automatic Control Design for Manufacture Design Methodology Finite Element Analysis Fluid Mechanics Heat Transfer Materials Mechanical Instruments Noise Sustainable Energy Systems and Technologies Vibration

Electromagnetic Propogation Embedded Systems Engineering Information Theory and Error Control Coding Introduction of Smart Grid Control Microprocessors Power Electronics and Drives Power System Protection Renewable Energy Systems

Automatic Control Design for Manufacturi Design Methodology Embedded Software Engineering Instrumentation and Control Noise Power Electronics and Drives Renewable Energy Principles Renewable Energy Systems Sustainable Energy Systems and Technologies Vibration

Table 15 - Curtin University Mechanical, Electronic and Communication and Mechatronics Engineering Course Content

Table 16 below compares the Curtin University mining, petroleum and mechatronics engineering course

content.114


Core Coal Mine Design and Feasibility Electrical Systems Engineering Foundations: Design and Processes Engineering Foundations: Principles and Communication Engineering Materials Engineering Mathematics Engineering Mechanics Engineering Programming Geology Hard Rock Mine Design and Feasibility Materials Handling Mathematics and Statistics Mechanics of Solids Mine Asset Management Mine Finance and Economics Mine Geotechnical Engineering Mine Management Mine Planning Mine Surveying and Mapping

Advanced Drilling Practices Advanced Reservoir Engineering Chemical Engineering Thermodynamics Chemistry Crude Oil Processing Drilling Engineering Drilling Fluids Laboratory Engineering Sustainable Development Field Development Design Project Fluid Mechanics Formation Evaluation Geology Hydrocarbon Phase Behaviour Introduction to Petroleum Engineering Numerical Reservoir Simulation Petroleum Production Technology Petroleum Economics, Risk and Project Management Petroleum Engineering Laboratory Petroleum Geology and Geophysics Petroleum Geomechanics Petrophysics Process Engineering and Analysis

Automatic Control Electrical Circuits Embedded Systems Engineering Engineering Graphics Engineering Law Engineering Management Engineering Mathematics Engineering Sustainable Development Foundations of Digital Design Linear Systems Modeling Machine Dynamics Manufacturing for Mechatronics Mechanical Design Mechatronic Automation Mechatronic Modeling Mechatronic Project Mechatronic Systems Design Power Electronics Professional Practice Unix and C Programming

114

http://engineering.curtin.edu.au/courses/ug_courses.cfm AND http://courses.curtin.edu.au/course_overview/undergraduate/mining-engineering

http://engineering.curtin.edu.au/courses/ug_courses.cfm


109


Mine Ventilation Mining Geomechanics Mining Research Project Mining Systems Mining and Metallurgy Resource Estimation Resource and Structural Geology Rock Breakage Socio-Environmental Aspects of Mining Surface Mining Systems Thermofluids Underground Mining Systems WASM Advanced Mine Ventilation

Process Instrumentation and Control Process Principles Reservoir Engineering Fundamentals Reservoir Property Mapping Simulation and Intervention Operations Strength of Materials

Optional Engineering Chemistry Engineering Physics Engineering: Its Evolution, Development, Success and Failures Introduction to Renewable Energy Materials and Technology

Automatic Control Design for Manufacturing Design Methodology Embedded Software Engineering Instrumentation and Control Noise Power Electronics and Drives Renewable Energy Principles Renewable Energy Systems Sustainable Energy Systems and Technologies Vibration

Table 16 – Curtin University Mining, Petroleum and Mechatronics Engineering Course Content

UNIVERSITY OF QUEENSLAND

Of the engineering curricula analysed in this section of the report, the University of Queensland appears to

have the greatest commonality in core units and electives between mechanical, electrical and mechatronics

engineering. Table 17 below compares University of Queensland course content in mechanical, electrical and

mechatronics engineering.115

Units Mechanical Engineering Electrical Engineering Mechatronics Engineering

Core Engineering Design Introduction to Electrical Systems Engineering Mechanics: Statics and Dynamics Engineering Thermodynamics Calculus and Linear Algebra Engineering Modeling and Problem Solving Multivariate Calculus and Ordinary Differential Equations Calculus and Linear Algebra II Structures and Materials Introduction to Engineering Design Machine Element Design Dynamics and Orbital Mechatronics Fundamentals of Fluid Mechanics Engineering Analysis

Engineering Design Introduction to Electrical Systems Calculus and Linear Algebra Engineering Modeling and Problem Solving Multivariate Calculus and Ordinary Differential Equations Introduction to Software Engineering Electromagnetism and Modern Physics Introduction to Computer Systems Electromechanics and Electronics Calculus and Linear Algebra II Computer Systems Principles and Programming Circuits, Signals and Systems Team Project Analysis of Ordinary Differential Equations

Engineering Design Introduction to Electrical Systems Engineering Mechanics: Statics and Dynamics Calculus and Linear Algebra O Engineering Modeling and Problem Solving Multivariate Calculus and Ordinary Differential Equations Introduction to Software Engineering I Electromagnetism and Modern Physics Introduction to Computer Systems Calculus and Linear Algebra II Structures and Materials Circuits, Signals and Systems Analysis of Ordinary Differential Equations Dynamics and Orbital Mechanics Mechatronic System Design Project I

115

http://www.engineering.uq.edu.au/current-students


110


Analysis of Ordinary Differential Equations Finite Element Method and Fracture Mechanics Thermodynamics and Heat Transfer Engineering Management and Communications Analysis of Engineering and Scientific Data Mechanical Systems Design Advanced Dynamics and Vibrations Fluid Mechanics Engineering Acoustics Engineering Analysis II Energy and the Environment Sensors and Actuators Introduction to Control Systems Professional Engineering Project Engineering Thesis Major Design Project

Probability Models for Engineering and Science Embedded Systems Design and Interfacing Signals, Systems and Control Electrical Energy Conversion and Utilisation Electronic Circuits Fundamentals of Electromagnetic Fields and Waves Thesis Project

Probability Models for Engineering and Science Electromechanics and Electronics Signals, Systems and Control Introduction to Control Systems Machine Element Design Advanced Dynamics and Vibrations Advanced Control and Robotics Sensors and Actuators Mechantronic System Design Project II Thesis/Design Project

Introductory Chemistry Mathematical Foundations Physical Basis of Biological Systems Chemistry for Science and Engineering Introduction to Software Engineering Introduction to Research Practices – The Big Issues Electromagnetism and Modern Physics Aerospace Materials Electrochemistry and Corrosion Electromechanics and Electronics Engineering Asset Management Engineering Acoustics Science and Engineering of Metals Engineering Analysis II Materials Selection Net Shape Manufacturing Aerospace Propulsion Energy and Environment Hypersonics and Rarefied Gas Dynamics Major Design Project Space Engineering Sensors and Actuators Advanced Control and Robotics Fundamentals of Technology and Innovation Management

Photonics Microwave Subsystems and Antennas Communications Systems Digital Systems Design Power Systems Analysis Advanced Electronic and Power Electronics Design Digital Signal Processing Image Processing and Computer Vision Introduction to Control Systems Advanced Control and Robotics Machine Learning Computer Networks Programming in the Large Special Topics in Electrical Engineering Power Systems Protection Modern Asset Management and Condition Monitoring in Power Systems Medical and Industrial Instrumentation Medical Imaging Engineering Mechanics: Statics and Dynamics Introduction to Systems Engineering Project Management Professional Practice and the Business Environment

Introductory Chemistry Mathematical Foundations Physical Basis of Biological Systems Computer Systems Principles and Programming Embedded Systems Design and Interfacing Fundamentals of Electromagnetic Fields and Waves Electrical Energy Conversion and Utilisation Electronic Circuits Engineering Thermodynamics Fundamentals of Fluid Mechanics Science and Engineering of Metals Thermodynamics and Heat Transfer Fluid Mechanics

Table 17 - University of Queensland Mechanical, Electrical and Mechatronics Engineering Content

The University of Queensland does not offer an undergraduate degree in petroleum engineering. Table X

below compares the University of Queensland course content in mining engineering and mechatronics

engineering.116

116

http://www.engineering.uq.edu.au/current-students AND http://www.engineering.uq.edu.au/mining

http://www.engineering.uq.edu.au/current-students


111


Core Engineering Design Earth Processes and Geological Materials for Engineers Engineering Mechanics: Statics and Dynamics Calculus and Linear Algebra Engineering Modeling and Problem Solving Multivariate Calculus and Ordinary Differential Equations Fluid Mechanics Introduction to Mining Structural Mechanics for Mining Analysis of Engineering and Scientific Data Fundamentals of Soil Mechanics Calculus and Linear Algebra II Resource Geology and Mine Surveying Physical and Chemical Processing of Minerals Resource Estimation Mining Geomechanics Mining Systems Mine Planning Mine Ventilation Rock Breakage Mine Geotechnical Engineering Mining Research Project Hard Rock Mine Design and Feasibility Mine Management Mining Research Project II Coal Mine Design and Feasibility

Not Available at the University of Queensland

Engineering Design Introduction to Electrical Systems Engineering Mechanics: Statics and Dynamics Calculus and Linear Algebra O Engineering Modeling and Problem Solving Multivariate Calculus and Ordinary Differential Equations Introduction to Software Engineering I Electromagnetism and Modern Physics Introduction to Computer Systems Calculus and Linear Algebra II Structures and Materials Circuits, Signals and Systems Analysis of Ordinary Differential Equations Dynamics and Orbital Mechanics Mechatronic System Design Project I Probability Models for Engineering and Science Electromechanics and Electronics Signals, Systems and Control Introduction to Control Systems Machine Element Design Advanced Dynamics and Vibrations Advanced Control and Robotics Sensors and Actuators Mechantronic System Design Project II Thesis/Design Project

Optional Introductory Chemistry Mathematical Foundations Physical Basis of Biological Systems Chemistry for Science and Engineering Introduction to Software Engineering Introduction to Electrical Systems Engineering Thermodynamics Introduction to Research Practices – The Big Issues Electromagnetism and Modern Physics Reaction Engineering Metallurgical Process Modeling Geotechnical Engineering Engineering Asset Management Energy Resources Ore Body Modeling Computational Fluid Dynamics Minerals Industry Visit Special Topics in Mining Underground Mining Systems Socio-environmental Aspects of Mining Surface Mining Systems

Introductory Chemistry Mathematical Foundations Physical Basis of Biological Systems Computer Systems Principles and Programming Embedded Systems Design and Interfacing Fundamentals of Electromagnetic Fields and Waves Electrical Energy Conversion and Utilisation Electronic Circuits Engineering Thermodynamics Fundamentals of Fluid Mechanics Science and Engineering of Metals Thermodynamics and Heat Transfer Fluid Mechanics


112


Mineral Processing II Mineral Processing: Geology Processes, Mineralogy & Comminution Circuit Design Advanced Mine Ventilation

Table 18 - University of Queensland Mining and Mechatronics Engineering Course Content

UNIVERSITY OF NEW SOUTH WALES

Table 19 below compares University of New South Wales course content in mechanical, electrical and

mechatronics engineering.117


Core Mathematics Higher Mathematics Physics Higher Physics Computing Engineering Design Engineering Mechanics Electric and Telecommunications Engineering Engineering Mathematics Numerical Methods and Statistics Engineering Design 2 Mechanics of Solids Fluid Mechanics Thermodynamics Mechanical Design Computational Engineering Advanced Thermofluids Linear Systems and Control Engineering Experimentation Engineering Mechanics Mechanics of Solids Mechanical Design F&A Vibration Professional Engineering Thesis A Thesis B Engineering Management

Mathematics Higher Mathematics Higher Physics Computing Higher Computing Introduction to Engineering Design and Innovation Data Structure and Algorithms Higher Data Structure and Algorithms Electrical Circuits Digital Circuit Design Circuits and Signals Embedded Systems Design Analogue Electronics Electromagnetic Engineering Electronics Digital Signal Processing Electrical Energy Control Systems Electrical Engineering Design Thesis A Electrical Design Proficiency Thesis B Strategic Leadership and Ethics

Mathematics Higher Mathematics Physics Higher Physics Computing Engineering Design Engineering Mechanics Electronic and Telecommunications Engineering Engineering Mathematics Numerical Methods and Statistics Engineering Design Mechanics of Solids Fluid Mechanics Thermodynamics Linear Systems and Control Engineering Mechanics Mechanics of Solids Model and Control of Mechatronics Systems Robot Design Elements of Mechatronic Systems Computer Applications in Mechatronic Systems Professional Engineering Thesis A Thesis B Engineering Management Advanced Autonomous Engineering Robotics

Electives Molecules, Cells and Genes Engineering in Medicine Biology Ecology, Sustainability and Environmental Science Sustainable Product Engineering and Design Chemistry A: Atoms, Molecules and Energy Higher Chemistry A: Atoms, Molecules and Energy Engineering Materials and Chemistry

Real Time Instrumentation Engineering Modeling and Simulation Software Construction Network Technologies Analogue and Digital Communications Trusted Networks Information, Codes and Ciphers Computational Mathematics Mathematical Methods and Partial Differential Equations Optimisation Dynamical Systems and Chaos

Molecules, Cells and Genes Engineering in Medicine Biology Ecology, Sustainability and Environmental Science Sustainable Product Engineering and Design Chemistry A: Atoms, Molecules and Energy Higher Chemistry A: Atoms, Molecules and Energy Engineering Materials and Chemistry Engineering Chemistry

117

http://www.eng.unsw.edu.au/information-for/current-students/undergraduates/course-program-outlines


113


Engineering Chemistry Chemistry B: Elements, Compounds and Life Higher Chemistry B: Elements, Compounds and Life Computing 1B Engineering Mechanics for Civil Engineers Engineering Mechanics (Mech) Environmental Principles and Systems Electrical and Telecommunications Engineering Fundamentals of Geology Fundamentals of Petroleum Geology Land Resource Assessment Surveying and GIS 1 Discrete Mathematics Mineral Resources Engineering Higher Physics 1B Psychology 1 A Introduction to the Petroleum Industry Sustainable Energy

Fluids, Oceans and Climate Computer Architecture Operating Systems Microelectronics Digital and Embedded Systems Microelectronics Design and Technology Solid-State Electronics RF Electronics Energy Systems Power Systems Equipment Power Systems Analysis Electrical Drive Systems Power Electronics Signal Processing Advanced Digital Signal Processing Multimedia Signal Processing Biomedical Instrumentation, Measurement and Design Systems and Control Continuous-Time Control System Design Computer Control Systems Real Time Engineering Data and Mobile Communications Wireless Communications Technology Mobile and Satellite Communications Systems Digital Modulation and Coding Network Performance Photonics Optical Circuits and Fibres Photonic Networks Business Administration Entrepreneurial Engineering

Chemistry B: Elements, Compounds and Life Higher Chemistry B: Elements, Compounds and Life Computing 1B Engineering Mechanics for Civil Engineers Engineering Mechanics (Mech) Environmental Principles and Systems Electrical and Telecommunications Engineering Fundamentals of Geology Fundamentals of Petroleum Geology Land Resource Assessment Surveying and GIS 1 Discrete Mathematics Mineral Resources Engineering Higher Physics 1B Psychology 1 A Introduction to the Petroleum Industry Sustainable Energy

Table 19 - University of New South Wales Mechanical, Electrical and Mechatronics Engineering Content

Table 20 below compares the Curtin University mining, petroleum and mechatronics engineering course

content.118

The University is currently contemplating integrating a mechatronics stream of electives into its

mining engineering program.


Core Mathematics Higher Mathematics Physics Higher Physics Computing Computing for Engineers Introduction to Engineering Design and Innovation Mining Services Engineering Mathematics Mining Project Development Mechanics of Solids

Mathematics Higher Mathematics Physics Higher Physics Computing Computing for Engineers Engineering Design and Innovation Engineering Materials and Chemistry Introduction to the Petroleum Industry Fundamentals of Petroleum Geology Introduction to Petrophysics Chemical Engineering Fundamentals

Mathematics Higher Mathematics Physics Higher Physics Computing Engineering Design Engineering Mechanics Electronic and Telecommunications Engineering Engineering Mathematics Numerical Methods and Statistics Engineering Design

118

http://www.eng.unsw.edu.au/information-for/current-students/undergraduates/course-program-outlines


114


Numerical Methods and Statistics Introduction to Fluid Flow and Heat Transfer Minerals and Processing Resource Estimation Mining Geomechanics Mining Systems Socio-Environmental Aspects of Mining Mine Planning Mine Ventilation Rock Breakage Hardrock Feasibility Project Mine Geotechnical Engineering Mining Research Project 1 Coal Feasibility Project Mining Research Project 2 Mine Management

Reservoir Engineering Business Practices in the Petroleum Industry Engineering Mathematics Field Development Geology and Geophysics Well Drilling Equipment and Operations Petroleum Economics Reservoir Characterisation and Simulation Design Project for Petroleum Engineers Formation Evaluation Thesis A Enhanced Oil and Gas Recovery Natural Gas Engineering Integrated Oil and Gas Field Evaluation Well Technology Petroleum Production Engineering

Mechanics of Solids Fluid Mechanics Thermodynamics Linear Systems and Control Engineering Mechanics Mechanics of Solids Model and Control of Mechatronics Systems Robot Design Elements of Mechatronic Systems Computer Applications in Mechatronic Systems Professional Engineering Thesis A Thesis B Engineering Management Advanced Autonomous Engineering Robotics

Elective Engineering Mechanics Mineral Resources Engineering Fundamentals of Geology Engineering Materials and Chemistry Minerals and Processing Surface Mining Systems Underground Mining Systems Advanced Mine Ventilation Mining Asset Management and Services Mining in a Global Environment Advanced Geotechncial Engineering

Engineering in Medicine and Biology Ecology, Sustainability and Environmental Science Sustainable Product Engineering and Design Engineering Chemistry Fundamentals of Chemistry Higher Chemistry Higher Computing Engineering Mechanics Environmental Principles and Systems Electrical and Telecommunications Engineering Fundamentals of Geology Land Studies Surveying and GIS Mineral Resources Engineering Design for Manufacture Sustainable Energy Chemical Engineering Design Professional Issues and Ethics Microeconomics Macroeconomics Sedimentary Environments Specific Topics in Petroleum Geoscience Marketing Fundamentals Numerical Methods and Statistics Fundamentals of Management Drilling Fluids and Cementing Social Issues in Science and Technology Safety, Health and Environmental Management Systems Risk Assessment and Safety Engineering Risk Management

Molecules, Cells and Genes Engineering in Medicine Biology Ecology, Sustainability and Environmental Science Sustainable Product Engineering and Design Chemistry A: Atoms, Molecules and Energy Higher Chemistry A: Atoms, Molecules and Energy Engineering Materials and Chemistry Engineering Chemistry Chemistry B: Elements, Compounds and Life Higher Chemistry B: Elements, Compounds and Life Computing 1B Engineering Mechanics for Civil Engineers Engineering Mechanics (Mech) Environmental Principles and Systems Electrical and Telecommunications Engineering Fundamentals of Geology Fundamentals of Petroleum Geology Land Resource Assessment Surveying and GIS 1 Discrete Mathematics Mineral Resources Engineering Higher Physics 1B Psychology 1 A Introduction to the Petroleum Industry Sustainable Energy

Table 20 – University of New South Wales Mining, Petroleum and Mechatronics Engineering Course Content

UNIVERSITY OF SYDNEY

Whilst the University of Sydney is not recognised as a leading resources engineering school, its mechatronics

engineering degree program is relevant to this report firstly because it is highly regarded and secondly because

through the Australian Centre for Field Robotics (ACFR) the institution has significant links to the minerals


115

industry. The course content for mechatronics engineering at the University of Sydney is summarised in Table

21 below.119

It would appear that this course has a greater theoretical content than the other mechatronics

engineering programs discussed in this section of the report.

Units Mechatronics Engineering

Core Fundamentals of Electrical and Electronic Engineering Engineering Computing Differential Calculus Linear Algebra Introduction to Mechatronic Engineering Dynamics Engineering Mechanics Integral Calculus and Modelling Statistics Mechatronics 1 Materials 1 Engineering Dynamics Linear Mathematics and Vector Calculus Mechatronics 2 Mechanics of Solids Electronic Devices and Circuits Partial Differential Equations Mechanical Design 1 System Dynamics and Control Power Electronics and Applications Electronic Circuit Design Manufacturing Engineering Thermodynamics and Fluids Mechanical Design 2 Engineering Management Mechatronics 3 Engineering Project Practical Experience Professional Engineering 2

Electives Guidance, Navigation and Control Introduction to Biomechatronics Sensors and Signals Computers in Real-time Control and Instrumentation Experimental Robotics Computer Vision and Image Processing

Table 21 - University of Sydney Mechatronics Engineering Course Content

PROGRAMS FOR PRODUCTION PROCESS OPTIMISATION MANAGER

It has been the experience in both other industries and resources industry operations that have implemented

extensive automation programs that expertise in ‘whole-of-operations’ systems optimization is invaluable in

terms of achieving the maximum benefits of automation. The resulting position of production process

optimization manager is conventionally performed by individuals with a range of backgrounds including

technical professionals such as engineers or systems analysts, business analysts with accounting and/or

operational management backgrounds and military logistics expertise.

This role is common to industries such as manufacturing and transport, but is relatively new to most resources

industry operations. There are also limited options for holistic formal qualifications to support skills

119

http://sydney.edu.au/handbooks/engineering/undergraduate/schools/aeronautical_mechanical_mechatronic/mechatronic.shtml


116

development in this role, with most production process optimization managers having gained skills from

operational experience supplemented with short-courses in optimisation processes such as Lean Six Sigma.

As extensive automation systems are increasingly adopted in the resources industry, scope may emerge for

the development of a post graduate course for which managers with technical and business undergraduate

backgrounds can enroll to rapidly develop the fundamental skills in areas such as statistics and various process

and project management methodologies that underpin the expertise required in this role. Such a program

would be optimized if it was supported by a strong resources industry operations research group at a

university.

117

APPENDIX 1: AUTOMATION TECHNICIAN TASKS

The following table summarises tasks that would typically be performed by a resources industry automation technician. 120

Generic Tasks Generic Sub-tasks Field of Depth

IT Specific Tasks Electrical Specific Tasks

Process Control Specific Tasks

Hydraulic Specific Tasks

Pneumatic Specific Tasks

Functional Safety

Installation Accurately follow operating procedures Follow vendor information Follow engineering drawings Connect systems Documentation of modifications

Connecting wires and cables Addressing devices

Connecting wires and cables Addressing devices

Nil Install hoses and piping Install devices Install actuators Install safety devices

Install hoses and piping Install devices Install actuators Install safety devices

Follow procedures Understand isolation Risk assessment

Inspection and Test Verify design Documentation of modifications Reference vendor information Reference engineering drawings Document results

Check cables Addressing devices Check physical installation

Check cables Addressing devices Check physical installation Point to point wire testing Conductivity testing Insulation testing Check connectivity and termination Filling out test sheets

Nil Check hoses and piping Check physical installation Check connectivity and termination

Check hoses and piping Check physical installation Check connectivity and termination

Follow procedures and understand isolation Risk assessment

120

Mining Industry Skills Centre, Automation Technician Task Table


118


Recording results

Primary Power –up Isolation procedures Understand vendor information Document results Supply power

Fundamental boot-up Monitoring diagnostics

Monitoring diagnostics Measure power

Nil Secondary energisation Secondary energisation Follow procedures Understand isolation Risk assessment

Configuration Vendor information Set and record parameters Calibration

Install software Configure network parameters Configure device parameters

Install software Check connectivity Configure network parameters Configure device/sensor parameters


Test and Record Functionality (Pre-commissioning)

Document results Specific device functions Calibration

Check connectivity Direction test motor IO test Instrumentation tests


Secondary Energisation Isolation procedures Understand vendor information Document results Supply power

Nil Functionality check Nil Check and record parameters Visual and mechanical inspection

Check and record parameters Visual and mechanical inspection


System Functionality Check (Dry-commissioning)

Isolation procedures Understanding vendor information Document results

Nil Functionality check Operational sanity check

Loop tuning Functionality check

Functionality test Operational sanity check


Follow procedures Understand isolation HAZOP


119


Understand system functionality and interaction

System Functionality Check (Wet-commissioning)

Isolation procedures Understand vendor information Document results Understand system functionality and interaction

Nil Functionality check Operational sanity check

Loop tuning Functionality check



Follow procedures Understand isolation HAZOP

Modify and Upgrade (minor engineering task)

Engineering drawings Vendor information Test and document results Revision control Isolation

Software upgrades Firmware upgrades Hardware upgrades

Install, test and commission (all steps above as required)





Diagnose faults from a wide range of potential problems

Engineering drawings Vendor information Test and document results Revision control Isolation Follow standard fault finding procedures Perform basic data analysis Consult fault

Monitor diagnostics Test and measure





Nil


120


references Interact with product experts

Repair faults Engineering drawings Vendor information Test and document results Isolation

Install, test and commission (all steps as required above)





Nil

Support Technology Trials Log operational data Observe performance

Nil Nil Nil Nil Nil Nil

Perform Scheduled Maintenance

Performance logs Alarm and fault analysis Isolation Calibration Vendor procedures Replace, test and commission parts as required Recording software or configuration changes Revision control

Communication faults Fault logs

Test and measure parameters Test safety circuits Test overloads Measure motor current Replace, test and commission parts as required Visual inspections

Replace, test and commission parts as required

Replace, test and commission parts as required Take samples Test and measure Visual inspections

Replace, test and commission parts as required Change filters Take samples Test and measure Visual inspections

Interpret and Execute Plans Follow procedures Maintain control variables Log operational data



121


Observe performance

Gather Information and Develop Reports on Diagnosis and Solution

Log operational data Observe performance Write technical reports


TECHNOLOGY TYPES TO RECOGNISED FIELDS

Wireless data communication Optical fibre Antennae Routers/access points PLCs-DCS Embedded PCs Operating systems

Ranging sensors Lasers/radars Navigation sensors Encoders Resolvers Inertial sensors PC/Hard drivers

Field bus PLCs Embedded PCs SIL rated devices (Safety Integrity Level 0-3) Data acquisition tools

LVDT sensors

122

Resources Industry Training Council (RITC)

The RITC is a joint venture between the Chamber of Minerals and Energy of Western Australia (CME)

and the Australian Petroleum Production and Exploration Association (APPEA) that provides advice to

Government and industry on the workforce development needs and priorities of the mining, oil and

gas and downstream process manufacturing industries in Western Australia. The RITC is one of ten

Industry Training Councils operating in Western Australia that together form the Western Australian

Industry Training Advisory Network. All ten industry training councils are financially supported by the

Western Australian Department of Training and Workforce Development.

Established in 2009 following a State Training Board of WA review of industry advisory arrangements,

the RITC’s activities are based on consultation with industry and collaborative relationships with

enterprises, Government (at the State and Commonwealth levels), industry associations and

education and training institutions.

Each year the RITC undertakes a range of project based activity – focused on both “here and now”

issues and strategic “over the horizon” issues with a focus on workforce development/skilling

implications.

For more information on the RITC and its activities, visit www.ritcwa.com.au

http://www.ritcwa.com.au/


123

Australian Venture Consultants

Established in 2002, Australian Venture

Consultants (‘AVC’) is a solution driven

management consulting practice focused

on creating successful commercial

outcomes for innovative projects,

companies and institutions. AVC provides

its clients with a unique service based on

the insights it has acquired through

expertise and engagements in all elements

of the innovation ecosystem (see adjacent

figure).

AVC provides strategic planning and operational project management services to a range of clients including

ASX 100 companies, leading universities and research institutes, start-up and spin-out companies, investors in

technology and government policy-makers, particularly in the minerals and energy sectors.

Specific services provided to these clients include:

Technology roadmap development and research planning for industry, companies and research

organisations

Strategic and operational planning for innovation and knowledge based organisations

Technology commercialisation strategy and management

Intellectual property strategy and execution

Innovation management strategy and systems

Venture investment support

Government innovation policy and programs

Innovative education and training programs

Universities and ResearchInstitutes

Government Innovation Grant

Programs

Established Corporations

(Large and SME)New Companies

ProductMarkets

Venture Capital

Private Investors

Public Markets

Institutional Investors

Commercialisationand Product

Development

Marketing andBusinessStrategy

Innovation StrategyAnd Management

Systems

Innovation Finance

AVC’s engagement across a broad spectrum of innovative clients allows it to gather and share unique insights on strategic and operational innovation management issues

R&DManagement

and TechnologyTransfer