Andrew Campbell, Managing Consultant, Worley Parsons
Optimisation of Materials Handling Networks
u  Why Material Systems Matter?
u  Systems Modelling
§  Spreadsheets vs a “Model”
§  Greenfields Applications
§  Brow...
With 37,500 people in 166 offices throughout 43 countries, we
provide our customers with a unique combination of extensive...
Ø  Approximately 50-80% of Iron Ore costs are associated with materials handling and
transport from pit to customer
Ø  O...
Ø  System Wide Models
Ø  Spreadsheets
Ø  Discrete Event Simulation (Arena, ExtendSim etc.)
Ø  Used for project decisio...
Requirements?
Technology & Innovation?Interactions….
System Modelling – Spreadsheets vs DES model
Method Plus Minus
Spreadsheet •  Easy to build
•  Widely available tool
•  Gr...
Reclaim Rate tph Bin discharge tph Surge Bin Level
Reclaim Rate
15 min avg tph
Bin Discharge 15,000 tph - 7 min hatch chan...
Ø  Simulates supply chain and flow of
material (amongst other
applications!)
Ø  Typically model the following details
Ø...
1. Askaf Pit to Port DFS,
Mauritania
Xstrata
Complete pit-to-port model including
mine processing operations, stockpiling,...
Optimisation Process
Simulation
Data
Processing &
Presentation
Review
Results
Adjust
Model/New
Scenario
Data Collection
& ...
u  Base Metals Operation with significant amount of products stored for processing under
cover for environmental reasons
...
u  Mapped interdependencies between types of operations for each expansion scenario
u  Identified efficiency improvement...
u  Smelter Undergoing Brownfields Expansion
u  Required justification for performing incremental improvements
u  Modell...
Model vs. Actual Measured Furnace Levels
0
0.2
0.4
0.6
0.8
1
1.2
1.4
Level	
  (m)
Time
FF	
  Total	
  Level FF	
  Product	...
Example of Furnace Levels
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
Level	
  (m)
Time
EF	
  Product	
  Level EF	
  Total	
  Leve...
Monthly Predicted Concentrate Smelted vs. Plan
0
10,000
20,000
30,000
40,000
50,000
60,000
29/01/2011
23/04/2011
16/07/201...
Improved Performance on Plant Improvements
0
10,000
20,000
30,000
40,000
50,000
60,000
29/01/2011
23/04/2011
16/07/2011
8/...
Ø  Critical Component of System
Ø  Operator intervention required to clear
Ø  Examining structure response due to stati...
Chute Detailed Structural Assessment
Ø  Discrete Element Modelling
Ø  Good for detailed chute analysis,
reclaimers etc.
Ø  Generally required good material
...
Ø  Significant Experience in Designing Heavy Haul Ore, Coal
and Container Wagons
Ø  Specifically addressing fatigue issu...
u  Significant Experience in assisting clients in
procuring new cars
u  Use of Numerical Modelling (FEA) to
examine the ...
Ø  Significant amount of deposits below water table
Ø  Surface water may also be an issue
Ø  Material handling characte...
Automation for Mine Water
Overall Water Management Model
Supply, Demand, Monitoring, Adjusting to Conditions
Part of a Dyn...
u  Alumina being dissolved into hot
liquor below disc filter above
u  Issue with caustic mist being thrown
into atmosphe...
u  Particulate dropped through
left side
u  Mist and dust emissions
from the right
Material Being dropped into Liquor Ta...
Pulse	
  3
Pulse	
  2
Pulse	
  1
Pulsing Observed due to displacement of Air and Confinement within Tank
Commonly observed...
Air Quality Modelling
u  Important to consider the total system to ensure a change in one area doesn’t lead to limits
on your system elsewhere
...
Andrew Campbell, Worley Parsons, Optimisation of Materials Handling Networks
Upcoming SlideShare
Loading in...5
×

Andrew Campbell, Worley Parsons, Optimisation of Materials Handling Networks

332

Published on

Andrew Campbell delivered the presentation at 2014 Bulk Materials Handling Conference.

The 11th annual Bulk Materials Handling Conference is an expert led forum focusing on the engineering behind the latest expansions and upgrades of bulk materials facilities. This conference will evaluate the latest engineering feats that are creating record levels of throughput whilst minimising downtime.

For more information about the event, please visit: http://www.informa.com.au/bulkmaterials14

Published in: Engineering, Technology, Business
0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total Views
332
On Slideshare
0
From Embeds
0
Number of Embeds
1
Actions
Shares
0
Downloads
23
Comments
0
Likes
0
Embeds 0
No embeds

No notes for slide

Andrew Campbell, Worley Parsons, Optimisation of Materials Handling Networks

  1. 1. Andrew Campbell, Managing Consultant, Worley Parsons Optimisation of Materials Handling Networks
  2. 2. u  Why Material Systems Matter? u  Systems Modelling §  Spreadsheets vs a “Model” §  Greenfields Applications §  Brownfields Debottlenecking and Optimisation u  Examples of Detailed Modelling of Components u  Questions Contents
  3. 3. With 37,500 people in 166 offices throughout 43 countries, we provide our customers with a unique combination of extensive global resources, world-recognized technical expertise and deep local knowledge.
  4. 4. Ø  Approximately 50-80% of Iron Ore costs are associated with materials handling and transport from pit to customer Ø  Operators currently focussing on improving profit through looking at Ø  Volume Ø  Operating Costs Ø  Therefore there are large incentives in Ø  Identifying Bottlenecks and Addressing them Ø  Reducing Planned and Unplanned Downtime Ø  It is important to consider the System and its parts Why Materials Handling Systems Matter
  5. 5. Ø  System Wide Models Ø  Spreadsheets Ø  Discrete Event Simulation (Arena, ExtendSim etc.) Ø  Used for project decision making and production planning Ø  Process Models (Depends on the process) Ø  Key to understand interactions between competing requirements Ø  More Detailed Models Ø  Chute Design Packages (Empirical) Ø  Discrete Element Models (Bulk Material Flow Modelling) Ø  Computational Fluid Dynamics (Flow Modelling) Ø  Finite Element Analysis (Mechanical/Structural) Ø  Physical Models Ø  Above for operational issues, maintenance planning, RAM etc. are others that should be considered Ø  As for all modelling it is important to understand the underlying assumptions and effect on the results Ø  Level of Detail vs Accuracy è Cost & Schedule è What is required for engineering/risk management? Simulation Options for Materials Handling Systems
  6. 6. Requirements? Technology & Innovation?Interactions….
  7. 7. System Modelling – Spreadsheets vs DES model Method Plus Minus Spreadsheet •  Easy to build •  Widely available tool •  Great for Simple Models •  Difficult to Maintain, debug •  Becomes unwieldy for large systems Discrete Event Simulation •  Downtime and events can be accounted for in a statistical manner •  Ability to perform Monte Carlo Simulations for long run expected results •  Handles multiple grades/ products easily •  Modules can be created and re-used •  Up front investment in model required •  Requires more details regarding system and interruptions
  8. 8. Reclaim Rate tph Bin discharge tph Surge Bin Level Reclaim Rate 15 min avg tph Bin Discharge 15,000 tph - 7 min hatch change Bin Discharge 13,500 tph - 7 min hatch change Surge Bin Max Level Ø  Based on recorded stockyard reclaimer data Ø  Examining performance of surge bin to look at conveyor capacities and bottlenecking issues Ø  Surge bin makes significant impact in ship loading operations Spreadsheet Based Surge Bin for Ship Loading Circuit
  9. 9. Ø  Simulates supply chain and flow of material (amongst other applications!) Ø  Typically model the following details Ø  Port/Berth limitations/utilisation Ø  Rail Operations including tracks and passing loops Ø  Mine Operations Ø  Blending Ø  Stockpiling Ø  Weather Ø  Breakdowns Ø  Model allows many duplicate runs to be simulated to achieve long run average (Monte Carlo) Ø  And observe multiple constraints concurrently Ø  Virtual Simulator Discrete Event Simulation Models
  10. 10. 1. Askaf Pit to Port DFS, Mauritania Xstrata Complete pit-to-port model including mine processing operations, stockpiling, rail network, port landside and port marine operations 2. Matthews Ridge Transportation Scoping Study, Guyana Reunion Manganese High level transportation scoping study for preferred option 3. Weld Range BFS Mine Processing and Transportation, Australia SinoSteel Validation/optimisation of engineering, storage, product grade, crushing and screening operations 5. Browse LNG supply chain studies, Australia Woodside FEED supply chain studies for production, shipping fleet and onshore storage needs for new LNG facility 6 5 4 1 6. COREFCO FEED shed study, Canada Sherritt International Assess capacity and performance of material handling processes and crew utilisation in refinery feed sheds. Increased production by 35% for zero CAPEX 4. Singapore Re-Gas Facility, Singapore Singapore Government LNG storage requirements supply to domestic power markets for start-up and expansion cases 3 2 10 Achieving for our Customers
  11. 11. Optimisation Process Simulation Data Processing & Presentation Review Results Adjust Model/New Scenario Data Collection & Agree Assumptions Build Model Presentation Report, Further Engineering
  12. 12. u  Base Metals Operation with significant amount of products stored for processing under cover for environmental reasons u  Considered all delivery transport modes (shipping from a dozen global sources, rail from two sources, and trucking), over 26 product types and 46 storage options. Brownfields Optimisation – Multiple Products, Constrained Storage
  13. 13. u  Mapped interdependencies between types of operations for each expansion scenario u  Identified efficiency improvements, alternative delivery schedules and personnel utilisation u  Determined what storage was required to facilitate expanded throughput and additional constraints §  Existing site limited locations for new storage §  Caused further issues in transporting material to conveyors as Front End Loaders are use to move materials u  Identified procedural/scheduling changes were required to significantly reduce additional storage requirements (by up to 90%). Brownfields Optimisation – Multiple Products, Constrained Storage continued
  14. 14. u  Smelter Undergoing Brownfields Expansion u  Required justification for performing incremental improvements u  Modelling simulated smelting and refining rates §  Smelter feed as per production plan §  Regular maintenance set up on as per the planned maintenance and allowance for breakdowns also allowed §  Examined bottlenecks in current operation u  Key questions around §  Concentrate Storage capacity §  Furnace limitations §  Key operational risks – with the potential to give rise to significant downtime Brownfields Debottlenecking: Copper Blister Launder Transfer
  15. 15. Model vs. Actual Measured Furnace Levels 0 0.2 0.4 0.6 0.8 1 1.2 1.4 Level  (m) Time FF  Total  Level FF  Product  Level FF  Product  Level  (actual) FF  Total  (actual)
  16. 16. Example of Furnace Levels 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 Level  (m) Time EF  Product  Level EF  Total  Level Max  EF  Product  Level Max  EF  Total  Level 1 Day
  17. 17. Monthly Predicted Concentrate Smelted vs. Plan 0 10,000 20,000 30,000 40,000 50,000 60,000 29/01/2011 23/04/2011 16/07/2011 8/10/2011 31/12/2011 24/03/2012 16/06/2012 8/09/2012 1/12/2012 23/02/2013 18/05/2013 10/08/2013 2/11/2013 25/01/2014 19/04/2014 12/07/2014 4/10/2014 27/12/2014 21/03/2015 13/06/2015 5/09/2015 28/11/2015 20/02/2016 14/05/2016 6/08/2016 29/10/2016 tonnes/month Concentrate  Smelted  (Input) Concentrate  Smelted  (Model)
  18. 18. Improved Performance on Plant Improvements 0 10,000 20,000 30,000 40,000 50,000 60,000 29/01/2011 23/04/2011 16/07/2011 8/10/2011 31/12/2011 24/03/2012 16/06/2012 8/09/2012 1/12/2012 23/02/2013 18/05/2013 10/08/2013 2/11/2013 25/01/2014 19/04/2014 12/07/2014 4/10/2014 27/12/2014 21/03/2015 13/06/2015 5/09/2015 28/11/2015 20/02/2016 14/05/2016 6/08/2016 29/10/2016 tonnes/month Concentrate  Smelted  (Input) Concentrate  Smelted  (Model)
  19. 19. Ø  Critical Component of System Ø  Operator intervention required to clear Ø  Examining structure response due to static load during a blockage Ø  Biggest load Ø  Also can examine how it will react to dynamic loads/forces Ø  It is becoming more common to perform non-linear FEA analysis for these types of applications Chute Structural Assessment
  20. 20. Chute Detailed Structural Assessment
  21. 21. Ø  Discrete Element Modelling Ø  Good for detailed chute analysis, reclaimers etc. Ø  Generally required good material characterisation and model calibration to be effective Bulk Flow Analysis
  22. 22. Ø  Significant Experience in Designing Heavy Haul Ore, Coal and Container Wagons Ø  Specifically addressing fatigue issues Ø  Reducing mass and maximising load Ø  Instrumented and ore car Ø  Measuring axel loads, strain gauges and draw bar Ø  Collected data used to assist in FEA analysis of rolling stock to meet design specifications whilst optimising design for mass and cost Ore Car Capacity
  23. 23. u  Significant Experience in assisting clients in procuring new cars u  Use of Numerical Modelling (FEA) to examine the loads involved u  Fatigue is a key issue §  Requires attention and a key aspect of the design §  Fabrication, especially weld quality, needs to adhere to specifications Structural Design for Ore/Coal Cars
  24. 24. Ø  Significant amount of deposits below water table Ø  Surface water may also be an issue Ø  Material handling characteristics change significantly Ø  General Shipping Requirements Ø  maximum moisture levels Ø  Cohesion between particles Ø  Material sticking to transfer chutes and equipment leading to blockages Ø  Adequately replicating cohesion or “stickiness” factors for DEM modelling a challenge Ø  note that moisture can change through the system! Ø  Dewatering, reuse and disposal are a system in itself that impacts on material handling Water
  25. 25. Automation for Mine Water Overall Water Management Model Supply, Demand, Monitoring, Adjusting to Conditions Part of a Dynamic Cycle Water Management Plan Bore Control Pump Control Pump Control Level, Water Quality Pump Control Ground Water Surface Water In-Pit Water Potable WaterProcess Water Raw Water Central control in communication with remote modular units Disposal
  26. 26. u  Alumina being dissolved into hot liquor below disc filter above u  Issue with caustic mist being thrown into atmosphere causing OHS issue for workers u  Ventilation and extraction to capture the dust and mist used in conjunction with some modifications to optimise the process CFD for Disc Filter Dust & Mist Capture
  27. 27. u  Particulate dropped through left side u  Mist and dust emissions from the right Material Being dropped into Liquor Tank
  28. 28. Pulse  3 Pulse  2 Pulse  1 Pulsing Observed due to displacement of Air and Confinement within Tank Commonly observed within material handling systems
  29. 29. Air Quality Modelling
  30. 30. u  Important to consider the total system to ensure a change in one area doesn’t lead to limits on your system elsewhere u  Simulation tools provide a way to test what you system can do §  And what changes to the system will mean §  Optimise your focus for improvements u  Still there is value in examining components §  Different level of detail/accuracy Summary
  1. A particular slide catching your eye?

    Clipping is a handy way to collect important slides you want to go back to later.

×