Andre Gibson from Key Engineering discusses a multi-disciplinary approach to debottle necking processes.

1. A multi-disciplinary approach
to debottlenecking processes
André Gerard Gibson
Key Engineering Solutions

2. Agenda
1. Introduction – why?
2. Identification of the bottlenecks
3. New control philosophy implementation
4. Challenging designs
5. Sustainability
6. Demonstrate results

3. Why?
• Systems too difficult for users to understand
• Challenging to maintain over time
• Very complex
• “Black Box” implementations
• Automation negatively impacts stability
Common issues seen within the mining industry

4. Why use this approach?
• Simple to use & visualize
• Easy to maintain
• Standard methods used in process control
• Reduces variability and pushes active
constraint
Excellence = Quality x AcceptanceExcellence = Quality x Acceptance

5. Identifying the bottlenecks
Performance workshops
Prepare for the
workshop
Facilitate
workshop
Close-out
workshop
• Plan agenda & brainstorming activity
• Invite experienced operations personnel from all disciplines
• Send through any relevant details prior
• Explore opinions on issues limiting increased performance
• Question why they are an issue
• Ensure everyone has input
• Ask group for possible fixes
• Provide examples of automated solutions
• Summarise solutions from the group

6. Identifying the bottlenecks
Data analysis
• Break system down into
distinct areas
• Determine utilization
calculation for each
• Develop utilization histogram
Area Utilization calculation
Infeed % utilization = rate / max rate
Screening % utilization = average screen house bin level / nominal maximum level
Scrubbing % utilization = total rate / (max. line rate x number available lines)
Desands % utilization = % level in feed tank / nominal maximum level
Crushing % utilization = average crusher building bin level / nominal maximum level
Stacking % utilization = rate / max rate
Thickener % utilization = slurry export rate / maximum export capacity
Underutilized True when % utilization for all other areas is under an acceptable level (e.g. 85%)

7. Identifying the bottlenecks
Constraint utilization visualization
• Live representation of
previous histogram
• Provides real-time data
on current bottlenecks
• Easy to identify when the
bottleneck shifts
• Useful tool for
management decisions

8. Implementation – constraint control
Standard process control “tool chest”
• Proportional, integral &
derivative (PID)
controllers
– Simple feedback control
– Commonly implemented
in industry
– Easy to tune
– Only a set-point
required by operator

9. Implementation – constraint control
Standard process control “tool chest”
• Smith predictors
– Predicted process
variable w/ correction
(filter)
– Eliminates dead-time
(Delay)
– Allows for quicker PID
response

10. Implementation – constraint control
Standard process control “tool chest”
• Override control scheme
– Various PIDs controlling
the same equipment
– Minimum selector to
control active constraint
– CV limited for non-active
constraints
– Non selected loops
placed into manual mode

11. Implementation – constraint control
Putting it all together – Feed rate example
• Feed rate control for a conveying system with multiple feed points
• Large dead-time prior to each weightometer feedback
• Requirement to maintain consistent set-point tonnage
• Simple Smith predictor to mitigate dead-time
• Filter = 1st order model of process
• Delay = Weightometer dead-time (Delay3)
• Smith predictor with delayed PV input
from previous weightometer
• Delay1 = time between weightometers
• Delay4 = dead-time from feeder to
weightometer
• Set-point adjusted to cater for
peaks/dips from previous controller
• Same process as previous controller
• Correction for controller & process
variation maximized
• Reduced variability & maximum
performance
Design & implementation: 8 days
Commissioning: 2 hours

12. Implementation – constraint control
Putting it all together – screening example
Fines /
Final Product
Tertiary
Secondary
Desands
W
W
W
W
PID
PV
SP
CV
PID
PV
SP
CV
PID
PV
SP
CV
<
S S
PID
PV
SP
CV
PID
PV
SP
CV
PID
PV
SP
CV
S S
<
P
PV
SP
CV
P
PV
SP
CV
P
PV
SP
CV
• Six primary constraints to control
• Three secondary constraints to control
• Two separate feeder areas to control
Product
Feeders
Desands
Feeders
PID
PV
SP
CV
PID
PV
SP
CV

13. Challenging equipment designs
• With now tighter control, less risk of overloading
• Original designs come with generic assumptions that may not
always be true
• Equipment designs cater for worst case scenario. If you can control
the scenario, you can alleviate the risk
• Just needs a simple first principles engineering approach
Why can we challenge the design?

14. Challenging equipment designs
Examples of challenging designs
- Ore profile of
conveyor at capacity
- Torque & power
within design limits
- VSD max. frequency
of 50Hz
- Tripper designed for
10,000tph
- Tripper movement
speed 0.5m/s
- Conveyor speed
4.5m/s
- Transfer chute at
maximum capacity
- Increase VSD max.
frequency to 60Hz
- Reduction in profile
to 83.3%
- Reduce tripper speed
to 0.25m/s in VSD
- Allows increase in
maximum rate to
approx. 10,500tph

15. Sustainability
Excellence = Quality x AcceptanceExcellence = Quality x Acceptance
• Quality
– Invest time in philosophy design
– Tune all loops prior to
completion
– Cater for abnormal situations
– Provide visual implementation
of what is in control
– Develop “issues” log book for
operators and address problems
– Coach operators in best
methods to control
• Acceptance
– Prior to implementation, sit
with all operators
– Be open to feedback from
operators
– Make them feel like part of the
solution
– Never reject operator concerns,
even when incorrect

16. Results
• Reduction in
Standard Deviation
• Before: 1251
• After: 925.2
• Whilst there is no
increase in rate,
variability reduction
generated
confidence for step
change increase in
rate set-point

17. Results
• Reduction in
Standard Deviation
• Before: 3428
• After: 2476
• Increase in rate
• Before:
15,258tph
• After:
16,671tph

18. Conclusion
• Simple problems don’t require complex
solutions
• Method doesn’t require specialist
knowledge
• Great results can be obtained if correctly
planned, designed & executed
• Never underestimate the importance of
acceptance
• Always be willing to challenge constraints

19. Questions?
www.keyengineering.com.au