Embed Size (px)
Citation preview
A multi-disciplinary approach to debottlenecking processesAndré Gerard GibsonKey Engineering Solutions
Agenda
1. Introduction – why?2. Identification of the bottlenecks3. New control philosophy implementation4. Challenging designs5. Sustainability6. Demonstrate results
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
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
Identifying the bottlenecksPerformance 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
Identifying the bottlenecksData 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%)
Identifying the bottlenecksConstraint 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
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
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
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
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 daysCommissioning: 2 hours
Implementation – constraint controlPutting it all together – screening example
Fines /Final Product
Tertiary
Secondary
Desands
W
W
W
W
PID
PVSP
CV
PID
PVSP
CV
PID
PVSP
CV
<
S S
PID
PVSP
CV
PID
PVSP
CV
PID
PVSP
CV
S S
<
P
PVSP
CV
P
PVSP
CV
P
PVSP
CV
• Six primary constraints to control• Three secondary constraints to control• Two separate feeder areas to control
ProductFeeders
DesandsFeeders
PID
PVSP
CV
PID
PVSP
CV
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?
Challenging equipment designsExamples 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
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
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
Results
• Reduction in Standard Deviation• Before: 3428• After: 2476
• Increase in rate• Before:
15,258tph• After:
16,671tph
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
