Improving Bucketwheel Reclaimer Performance and Asset Integrity using SCADA Data

Improving BW Reclaimer Performance &
Asset Integrity using SCADA Data
Bulk Materials Handling
Conference, Perth
Mark Biggs
Adam 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:
AS4324.1
Conveyor live load (F)
Flooded belt (FF)
BW drive power
AS4324.1
Normal 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 tph
using 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 80 100 120 140 160
0
x 10
5
BW motor current
BW motor current (A)
Bincounts(frequency)
0 20 40 60 80 100 120 140 160
0
50
100
Cumulativesum(%)
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 90 180 270 360
0
500
1000
1500
2000
2500
3000
3500
4000
4500
5000
Slew passes at slew angle
Slew angle (deg)
Slewpassespermilliontonnesreclaimedperquadrant
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 ModelFinite Element Structural Model
LoadsLoads
Stress cyclesStress cycles
Fatigue life
calculation
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 data1 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
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

Improving Bucketwheel Reclaimer Performance and Asset Integrity using SCADA Data

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