Mark Biggs & Adam Mayers - Aspec Engineering - Assessing bucketwheel reclaimer performance and AS4324.1 compliance using SCADA Data

Improving BW Reclaimer Performance & Asset Integrity using SCADA Data

Bulk Materials Handling Conference, Perth

Mark BiggsAdam Mayers

Outline

Improving BW Reclaimer Performance & Asset Integrity

using SCADA Data

• Introduction / context

• Operating within design envelope of machine – AS4324.1 Compliance

o Using SCADA data to compare actual operating loads to design loads.

o Operating loads (conveyor live load, digging loads, etc).

o Machine balance monitoring.

• Capital Planning – When will the machine reach the end of its life?

o Fatigue damage monitoring.

• Improving throughput performance by monitoring SCADA

o Fundamentals of Operation

o Reducing trips and unexpected downtime.

o Alternative control philosophies

o Identify opportunities for performance improvements.

Bucketwheel Reclaimers

• Bucketwheel reclaimers are extensively

used in materials handling facilities in

Australia. Predominately slewing,

luffing, long travel machine.

• Large, expensive items of equipment.

Many new machines have been

constructed in last 5 years.

• Typically high required availability and

utilisation.

• Machines typically fitted with SCADA

system (Supervisory Control and Data

Acquisition).

• Data available to optimise performance

within design envelope of machine.

Challenge is to turn this Data into

useful Information.

• Approach can be applied to different

equipment types.


using SCADA Data

AS4324.1 Design Envelope

• AS4324.1 – 1995 is the Australian

Standard relating to ‘Mobile

equipment for continuous handling of

bulk materials’

• Specifies how machine structures are

designed for structural strength and

fatigue life.

• New revision to be released in 2015

• Vast majority of new machines in

Australia have been designed to this

standard.


using SCADA Data

AS4324.1 Load Combination Table 3.7 – Related to Fatigue and

Strength Design Loads, and SCADA Data

Rare loads and

accidents – strength

design

e.g.

- Flooded Belt

- Collisions

- Grounding

- Cyclone

Operational

loads used for

strength design

- Dead weight

- Conveyor

- Digging

- Dynamics

Loads used to

calculate fatigue

life of machine

structure

- Conveyor

- Digging

Abnormal operation

strength design

- High digging loads

- Slew bearing

jacking

Many of the loads can

be related to drive

torque, or production

rate which are data

logged by the control

system (SCADA

system)Improving BW Reclaimer Performance & Asset Integrity

using SCADA Data

Using SCADA Data to Compare Real Loads with AS4324.1

Luff cylinder forces:AS4324.1- Dead load

balance- Slew brg loads- Combined live

loads- Collisions

Belt weigher tonnes/hr:AS4324.1Conveyor live load (F)Flooded belt (FF)

BW drive powerAS4324.1Normal digging (U)Abnormal digging (UU)

Slew drive power and angle:AS4324.1- Lateral digging (S)- Lateral collision (FS)- No. Slew cuts for

fatigue

Bucketwheel boom

Counterweight


using SCADA Data

Example – Conveyor Live Loads

Live Load (F) is the normal operating load for strength design.

The load can be converted to tphusing the belt speed (green line)

Flooded Belt Load (FF) is the accidental load used for strength design

Measured conveyor throughput is below strength design envelopes.

Fatigue design to AS4324.1 is based on 0.8 x (F) = 15,113 tph

Conclusion: Conveyor live load is within strength and fatigue design envelopes during this SCADA data sample.


using SCADA Data

0 20 40 60 80 100 120 140 1600

x 105 BW motor current

BW motor current (A)

Bin

counts

(fr

equency)

0 20 40 60 80 100 120 140 1600

50

100

Cum

ula

tive s

um

(%

)

Cumulative sum

AS 4324.1 fatigue digging CU.U

Motor full load current 108 A

AS 4324.1 normal digging U 175 kN

AS 4324.1 abnormal digging UU 239 kN

Example – Digging Loads A histogram is useful for large data

sets as it gives an idea of the

amount of time at each load level.

Green line represents digging load used in fatigue calculations.

Blue line represents Normal Digging Load (U) used in strength design.

Conclusion: Digging load is higher than assumed in the fatigue design which may reduce the life of certain areas of the structure. The loads are generally within the strength design envelope

Magenta line represents the Abnormal Digging Load (UU) used in strength design.


using SCADA Data

Example – Luff Cylinder Loads

The combined effect of the live loads can be seen in the luff cylinder pressures/loads.

We can also infer information about the dead load balance e.g. counterweight trim compared to design.


using SCADA Data

Example – Luff Cylinder Loads

Machine is slightly discharge boom heavy compared to design balance (green line)

Peak tensile luff cylinder loads approach the AS4324.1 III/6 Flooded Belt and Blocked Chute Combination but are inside the strength envelope (red dotted line)

Loads exceed the fatigue design assumptions quite often (blue line) Conclusions:

- Strength OK.- May need CW trim- Fatigue life may be shorter than design


using SCADA Data

Capital Planning – Remaining Fatigue Life

• Machines specifications typically require 20 years of operation or perhaps

100,000 operating hrs. Typically, primarily limitation on life of machine

structure is accumulated steel fatigue damage which results in cracking, at

which point, machine replacement is often required.

• Fatigue is caused by stress fluctuations at the welds. The magnitude of the

stress range and the number of cycles are important.

• For a Bucketwheel Reclaimer, the stress fluctuations and cycles are mainly

proportional to the number of slew cuts i.e. the digging and conveyor load

cycles, and magnitude of loads. The designer therefore converts the 20 year

life requirement to a number of slew cut cycles for the fatigue design

calculations. The conversion is based on the annual throughput rate,

stockpile shape and digging parameters.

• SCADA data can be analysed to count the number of slew cuts that actually

occur per million tonnes reclaimed and estimate the magnitude of loads, to

estimate remaining life based on historical throughput data.


using SCADA Data

Example – Remaining Fatigue Life

0 90 180 270 3600

500

1000

1500

2000

2500

3000

3500

4000

4500

5000Slew passes at slew angle

Slew angle (deg)

Sle

w p

asses p

er

million t

onnes r

ecla

imed p

er

quadra

nt

Statistic can be calculated for number of slew cuts per million tonnes reclaimed e.g. 4,300 slew cuts per Mt


using SCADA Data

Example – Remaining Fatigue Life

Historical production records converted to accumulated slew cuts e.g. 4,300 x annual production.

Variations in the production rate are captured.

Current point in time

Estimated point in time when the design fatigue life will have been consumed.

Suited to longer term capital planning i.e. approximate machine replacement


using SCADA Data

Example – More Detailed Fatigue Assessment

SCADA analysis and FEA can be used

together to derive stress/cycle

distributions as inputs to fatigue life

calculations.

More accurate because it includes the

load variations and cycles.

Suited to life extension studies and

targeting resources for asset integrity

inspections.Finite Element Structural Model

Loads

Stress cycles

Fatigue life

calculation


using SCADA Data

Improving Performance - Fundamentals of Operation

Re-positioning Losses at ends of cut

Trips result in production losses

Geometric & Control opportunities


using SCADA Data

Example – Modifying the Geometry of the Reclaim Process

SCADA data review and subsequent reclaim simulation indicated that a Stacker-Reclaimer was under-performing. One suggested change including moving from 4 bench to 3 bench reclaiming –estimated 10% improvement in average reclaim rate.

Change implemented in early 2015. SCADA review confirmed approx. 10% increase in average rate!


using SCADA Data

Example – Troubleshooting Trips to Minimise Production Delays

using 3D Graphics: Slew Clutch Alarms

Colour scale shows SCADA parameter as a function of 3D boom tip position e.g. BW current, throughput, slew torque

Black dots are logged alarms/trips which represent production delays (lost revenue) Concise way of finding patterns using very large data sets e.g. ~5 million data points in picture

below Easy to see that trips mainly occur at outer edges of lower benches using this technique Not easy to look at these patterns using normal “trend” software

1 month of 1Hz data


using SCADA Data


using 3D Graphics: Slew Clutch Alarms

Trips occur when slew speed is changing

quickly.

Zooming in on individual trips found that

the slew brakes were being applied

incorrectly.

Brake always applies before

trips


using SCADA Data


using 3D Graphics: Luff Cylinder Trips

Machine balance is boom heavy

Luff cylinders trip the machine due to

spikes in the digging load

Each black dot is a trip which stops the

machine until it is re-set. The average

delay is 3 mins

195 alarms in 90 days

195 alarms x 3 mins x 8,500 tph x $60/t =

$5M potential lost revenue per quarter

$20M annualised

195 trips

Trip frequency vs

duration


using SCADA Data



Add 2 tonnes to counterweight

Trips reduce from 195 to 69


using SCADA Data



Add 8 tonnes to counterweight

Trips eliminated

Need to do more struct/mech design checks, but

~5% mass increases are likely ok if machine is

originally compliant with AS4324.1


using SCADA Data

Example – Identification of Repositioning Losses

12 second delay between weightometer and BW. Consider incl. some BW torque feedback or relocate weightometer.

Significant repositioning losses, particularly at far end of slew cut.


using SCADA Data

Additional Opportunities

• Throughput measurements typically lag behind reclaim operation → slows control

system response. Alternative more direct feedback, such as bucketwheel current

or torque arm feedback control can be effective.

• Using SCADA data to benchmark performance against similar machines in fleet.

Recent example showed two identical machines were performing differently:

Reclaimer 1 average = 2815 TPH, Reclaimer 2 average = 3050 TPH → 8%

difference.

• Learn mode algorithms can be implemented to provide predictive feedback based

on SCADA data. Control of one slew reclaim cut is influenced by previous slew

reclaim cuts (e.g. pile edges, soft / hard sections of stockpile etc).

• Good stacking is very important!


using SCADA Data

Summary – Benefits of SCADA based Engineering Analysis

Asset Management

• Understand whether operating machines are compliant with AS4324.1

• If not full compliant, risks can be explored

• Targeting structural integrity inspections to fatigue prone areas

• Understanding machine balance via the luff cylinders.

Capital Planning

• Estimate when machine may need to be replaced in the future based on

remaining fatigue life.

Production

• Reduce production losses due to overload trips

• Identify under-utilisation within the design envelope and opportunities to

increase production rates.

• Benchmark production performance against similar machines in the fleet

• Highly cost effective method of “sweating the assets” for maximum productivity.


using SCADA Data

Thank you!


using SCADA Data

Business

Mark Biggs & Adam Mayers - Aspec Engineering - Assessing bucketwheel reclaimer performance and AS4324.1 compliance using SCADA Data