UNLOCKING THEHIDDEN POTENTIAL OF MANUFACTURINGLeveraging new lubricant technologies to boost productivity

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CONTENTS

1. INTRODUCTION 3

2. WELCOME TO THE FUTURE 4

3. SENSOR-BASED TECHNOLOGIES 5

4. BIG DATA-BASED TECHNOLOGIES 6

5. CLOUD-BASED TECHNOLOGIES 7

6. WHAT THE FACTORY OF THE FUTURE COULD LOOK LIKE 8

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INTRODUCTIONTowards the end of 2017, the UK manufacturing climate peaked and factories saw orders jump to the highest level in nearly 30 years1. Manufacturers were driven to accelerate output and reduce downtime, while meeting demands and maintaining product quality.

However, this time in the sun may prove to be short-lived, as uncertainty continues to linger. Brexit negotiations, coupled with the rise of protectionist governments around the world, may hamper growth.

As such, it remains important for manufacturing companies to find ways to increase productivity and profitability while maximising savings.

Many are already aware that monitoring Total Cost of Ownership (TCO)2 is important when it comes to extracting the best possible value from their equipment assets.

However, many often underestimate the importance of lubrication, even though the cost of lubricants accounts for around 1% to 2% of a manufacturing company’s total maintenance expenditure.

Building on the global Shell Lubricants 2017 report titled ‘Unlocking The Hidden Potential Of Manufacturing’3, this paper will highlight the second of three areas that UK manufacturers should address with respect to lubricants: leveraging new lubricant technologies to boost productivity. Other papers in this series explore how to prioritise the role of lubricants in your business, and how to educate and upskill employees on TCO.

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WELCOME TO THE FUTURE

‘The fourth industrial revolution’, or Industry 4.0 is upon us. The vision of an interconnected manufacturing facility with ‘intelligent’ communication between machines that make their own decisions is fast becoming a reality.

The rise of this smart, connected factory allows for optimisation at every stage of the production line. One important element of this, when considering business profitability, is that companies can benefit from added TCO savings as technology allows for manufacturers to take pre-emptive action. For instance, by leveraging Industry 4.0 technologies such as sensors, manufacturers can move from laboratory analysis to real-time, onsite lubricant health monitoring. This in turn helps maintain equipment longevity, and avoids unplanned downtime and loss of production4.

However, Shell Lubricants has found that not all UK manufacturers have taken full advantage of these technologies.

Only half (53%)5 say they adopt Industry 4.0 technologies in their manufacturing plants, potentially due to the lack of understanding and awareness of these technologies.

This next section will look at explaining three technologies of particular interest to the manufacturing sector – sensor, big data and cloud-based technologies – and highlights the benefits related to their adoption.

TECHNOLOGY TYPES IMPACTING THE MANUFACTURING SECTOR

SENSOR-BASED TECHNOLOGIES

Devices that detect and respond to some type of input from the physical

68% have implemented these

CLOUD-BASED TECHNOLOGIES

Retrieve resources from the internet through web-based tools

58% have implemented these

BIG DATA-BASED TECHNOLOGIES

Extremely large data and the technology to analyse and reveal patterns, trends and associations

42% have implemented these

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SENSOR-BASED TECHNOLOGIES

61% Increased productivity

37%Extended equipment life

36%Reductions in unplanned downtime/unexpected systems failures

36%Increases in operational efficiency

SENSOR-BASED TECHNOLOGIESSensor-based technologies6 offer an opportunity to upgrade equipment maintenance practices and realise greater TCO savings. They can self-test, validate, adapt, identify and understand the environment they are in, while managing a wide range of conditions. These technologies see the most benefit when applied to inaccessible or unmanned machinery.

Manufacturers in the UK are opting for real-time, on-site lubrication health monitoring, with 68% saying they use sensor-based technologies, instead of waiting for the analysis to take place in laboratories.

Using sensor-based technologies means that lubricants are now replaced or replenished based on their ‘true condition’. Traditionally, manufacturers would have depended on theory, such as the number of hours used, which would often result in the premature or delayed replacement of the lubricant. This can risk the overall health of the equipment, potentially leading to equipment failure and resulting maintenance costs.

As sensors provide real-time readings, including friction, wear and tear and lubricant condition, manufacturers are now able to plan for predictive maintenance. Upon detecting contamination or early stage lubricant degradation, sensors can alert maintenance staff of the need to intervene before the problem worsens, thereby helping avoid costly unplanned breakdowns.

There are many sensor types available for machine-specific applications. Some of the most common devices used in machine predictive maintenance are7:

– Vibration sensors: monitor the acceleration present during machine operation, and are the best starting point when developing a predictive maintenance strategy

– Temperature sensors: monitor critical machine components or auxiliary systems to detect changes in machine condition

– Oil particle sensors: monitor the level of particle contamination present in lubrication systems

– Flow sensors: monitor the flow rate of lubrication or cooling water flow

– Current sensors: monitor the current draw of machine components

– Humidity or moisture sensors: monitor the water content in hydraulic and lubrication oils

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BIG DATA-BASED TECHNOLOGIES

31%Lack of understanding around how to introduce connective technologies

31%Data security issues (e.g. loss of sensitive data)

30%Lack of standards around the use of connective technologies makes adoption difficult

BIG DATA-BASED TECHNOLOGIESWith the adoption of sensor technologies comes an increase in data that covers all stages in the life of a product or an asset. If used effectively, ‘big data’ can allow manufacturers to amass TCO savings. However, Shell Lubricants has found that in the UK, one in three (31%)5 manufacturers lack understanding around how to introduce big data-based technologies.

Big data is another way in which technology can facilitate a proactive approach to preventative maintenance. UK manufacturers understand that the right use of big data technologies can lead to increased operational efficiency (38%)5, improved quality control of fabricated or manufactured goods (33%)5, and increased revenue generation (30%)5.

Real-time telemetry that details various aspects of the production process allows for manufacturing companies to predict when machines will fail with extreme accuracy.

Shell LubeAnalyst, for example, processes and compiles huge quantities of data which can then be used to generate accurate reports that help monitor a stationary or mobile equipment’s oil over time. This helps identify performance issues that could prevent costly breakdowns, and more importantly optimise oil drain intervals.

While big data has its benefits, there is still some uncertainty about the potential risks. These include concerns around data security issues (31%)5,and a lack of standards around the use of big data-based technologies (30%)5.

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CLOUD-BASED TECHNOLOGIES

38%Increases in operational efficiency

33%Improve quality control of fabricated/manufactured goods

30%Enable my company to achieve greater profits

CLOUD-BASED TECHNOLOGIES In today’s fast-paced and increasingly complex industry, many manufacturers are finding that traditional Enterprise Resource Planning (ERP) systems are proving insufficient due to relatively high operating costs, restricted access to data, and limited functionality.

The introduction of cloud-based technology into manufacturing means that companies can store large amounts of data in the cloud. As such, anyone on the supply chain is privy to information, in real time, spurring manufacturers to become more agile and efficient, and encouraging them to quickly adapt to changing demands. By storing information in the cloud -- as a secondary data centre or ‘recover site’ -- manufacturing companies need not worry about the loss of vital information should they face a disaster, such as an industrial fire. As such, a shorter period of time would be needed to get the factory up and running again.

Used correctly, cloud-based technology has enormous potential to help enhance manufacturing production and performance. Weaving in big data, manufacturing companies can glean actionable insights through predictive analytics, such as ensuring lubrication quality and improvements or preventative maintenance, giving them an edge over competitors.

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1 http://www.thisismoney.co.uk/money/news/article-5104203/Manufacturers-strongest-orders-30-years.html

2 Total Cost of Ownership (TCO) is defined by Shell Lubricants as the total amount spent on industrial equipment, including cost of acquisition and operation over its entire working life, including costs of lost production during equipment downtime

3 This study into lubrication procedures in the manufacturing industry was commissioned by Shell Lubricants and conducted by research firm Edelman Intelligence. It polled 493 manufacturing industry staff who purchase, influence the purchase or use lubricants / greases as part of their job across 8 countries (Brazil, Canada, China, Germany, India, Russia, UK, US)

4 Bosch Rexroth: Industry 4.0: Connected Automation Starts Now

5 This survey, commissioned by Shell Lubricants and conducted by research firm Edelman Intelligence, is based on 100 interviews in the UK Manu-facturing sector with Senior Engineers, Operations Directors and Procurement Managers from UK manufacturing companies in December 2016

6 Defined as to sensors that are used to monitor equipment condition, level of production completion, etc.

7 The Manufacturer – Predictive maintenance sensors and implementation

8 Defined as software to interpret data gathered on the plant floor

9 Defined as software to securely store valuable data and access it without the need for physical storage space / hardware

THINK OF WHAT THE FACTORY OF THE FUTURE COULD LOOK LIKE IN THE NEXT FIVE TO 10 YEARS WHEN NEW TECHNOLOGIES CONVERGE:

Diverse global manufacturing sites equipped with real-time sensors to monitor oil condition

Information remotely feeds into a database that interprets the performance of the oil and flags potential issues. This information will guide real-time decision-making

Online and artificial intelligence-based resources provide instant access to critical lubricant knowledge and application expertise, no matter the location

Automated information about product selection, and potential cost improvement measures around lubricant selection or application, will be made.

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