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Research and Innovation in the Copper Sector
Presentation to the Copper to the World – Delivering South Australia’s Copper Strategy June 2017
Overview
• Synergy between innovation and research
• Mining - large scale underground
• Processing
• Integrated Operations
University of Adelaide 2
Synergy between Innovation and Research
• “creative and systematic work undertaken in order to increase the stock of knowledge and to devise new applications of available knowledge”
University of Adelaide 3
• “deliberate application of information, imagination and initiative in deriving greater or different value from resources, and includes all processes by which new ideas are generated and translating into useful products”
Innovation
Research OECD
Collaboration between Innovation and Research
University of Adelaide 4
Mining Companies
Technology Suppliers (METS and Start-ups)
ResearchProviders
Research Outcomes & Technology Transfer
• Challenges• Specifications• Implementation
• Fast Win; Fast Fail• Impacts Assessment
• Stock of knowledge• Qualified people
Government
Mining–Accelerated Development
–Fragmentation
–Underground Automation
–High Productivity Mining• Finer fragmentation
• Increased haulage and drawpoint rate
• Further exploits benefits of automation
–Grade Engineering®
–Pre-concentration
University of Adelaide 5
Impact of Innovation on Mining- Accelerate development – Earlier access to ore- Increase Return on Investment
University of Adelaide
6
Year Advance rateM per day
1980 15
2001 7.2
2011 3.8
2016 2.6
Target Advance Rates
• Decrease in Advance rate in spite of large and sophisticated equipment
• Focus not on the production system as a whole
DecreaseInvestment
AccelerateRevenue
IncreaseNPV
Pr
e-p
ro
du
cti
on
an
d P
ro
du
cti
on
Ca
sh
Years
RapidDevelopment
NormalDevelopment
Impact of Innovation on Mining- Accelerate development – Earlier access to ore- Increase Return on Investment
University of Adelaide 7
TemporaryCanopy
• Reduce Development Cycle time from >16 hours to <10.5 hours• Reduce face cycle ~ 8 hrs• Reduce muck cycle ~2 hours by rapid transport of rock
Mining – Fragmentation affects Productivity from Draw Points, Mucking and Hauling and Downstream
University of Adelaide 8
1. Fragmentation – depending on joint spacing and stress, the
need for preconditioning & large draw points
2. Dilution –Dilution and mud rushes between large rocks
3. Caveability - Lifts needed to prevent deviation of cave
4. Recovery – Depending on dip, footwall may be left
Cave TrackerBeacons and detectors
Sublevel CavingSteep dip and continuing to depthHigh development costs
Block Caving
Mining – Fragmentation affects Productivity from Draw Points, Mucking and Downstream
University of Adelaide 9
Draw Point Productivity t/m2 per day • Reducing Powder Factor to reduce mine costs• Less Jointed and Harder Ore• Concept that SAG milling needs coarse particles• Mucking rate reduced• Hanging due to coarse particles
Courtesy Fidel Baez
Hart, S, et al (2001) Optimisation of the Cadia Hill SAG Mill Circuit. Proc. Int. Conf. Autogenous and Semi-autogenous Grinding Technology, vol 1, pp.11-30.
Mining – Fragmentation affects Productivity from Draw Points, Mucking and Hauling
University of Adelaide 10
Continuous MiningAutonomous Continuing Mining
• Autonomous CMS implemented by optical sensing and control to maximise ore drawing plus achieve a uniform load on Panzer
• 22% increase in d50 rock size decreased productivity by 43% for non-autonomous
• Autonomous increased production by 30% for both coarse and fine rock distribution
• Conditions which increased interactions in flowing zones gave less rock hang ups and increased drawpoint productivityCastro, R., et al. (2015). "Automation fundamentals of continuous mining system."
International Journal of Mining, Reclamation and Environment 29(5): 419-432.
Underground Automation
University of Adelaide 11
• Real-time tracking of equipment
• Equipment and production data
• Draw control important to Sublevel Caving
• Production over shift change and during blasting
• Less damage to equipment
Mining – High Productivity Methods
University of Adelaide 12
High capital cost requiring thousands of metres of tunnel
Several blasting cycles required to establish drawbell &
undercut, damaging surrounding rock mass
Each blasting event requires remedial ground support
Slow cave establishment
Undercut drill horizon
• Untried concept but technology for method exists today• Rock mass above cave is conditioned after production blast• Post conditioning holes initiated after production holes• Wireless initiators required for this method• Blast wave reflections off free face• Post conditioning increases cave establishment rate, thus NPV
Post Conditioning using Wireless Initiation
MPa8
MPa4
MPa20
MPa30
MPa8
MPa4
MPa20
MPa30
• Wave reflects as a tensile wave with higher magnitude• Reflected tensile wave superimposed on incoming tensile wave• Superposition has magnitude higher than tensile strength
Conventional Sub-level Caving
Grade Engineering®
• Reject below cut off grade material in
stages of rock handling
• Amenability to upgrading
determined in core analysis and
distributed across resource
• Accentuate upgrading through
selective fragmentation (e.g.,
differential blasting)
• Grade Engineering® value optimised
with re-scheduling to exploit new
block model attributes constrained
by operational parameters
• Sensing and sorting depends on
mineralisation – poly-minerals and
dispersement in fragmentation
University of Adelaide 13
Ore Zones amenable to Grade Engineering® through Differential
Blasting
Mary Kathleen Uranium – Mary K – Radiometric Ore Sorter for U3O8
Scintillometer – Gamma Radiation plus Optical Detector for Particle Size
Stream U3O8
Grade (ppm)
U3O8
Recovery(%)
Mass Recovery(%)
Feed 1300 100 100
Reject 120 6 55
Pre-concentrate 2700 94 45
• Jaw Crush to -150 mm• +40 mm to Ore Sorting• -40 mm and Pre-concentrate
report to Fine Crushing• -40 mm higher grade
Pre-concentration
Stream Pb Zn Mass Recovery (%)
Feed 5 7 100
Reject 0.7 0.9 32
Pre-concentrate 7 10 68
Recovery (%) 95 96 -
• 14 mm top size• Feed Preparation – 1.7 mm• Throughput >1000 tph• -1.7 mm higher grade
Mount Isa Mines– Lead/Zinc – Heavy Medium Plant
University of Adelaide 14
Processing– Fine crushing and grinding to liberation size
• High Pressure Grinding Rolls
• Stirred mills with graded charge
• On-line Screen Efficiency
• Mill slurry and media volumetric load sensors
• Hydrocyclone sensors
– Flotation
• Integrated froth sensors for mass pull control
• Liberation sensor to maximise mill throughput
• Coarse particle recovery
– Leaching (Tank, Heap, Dump)
• Robust sensing and optimisation
• Bioleaching
– Product Handling
. Thickener 3d slurry density sensing
University of Adelaide 15
Integrated Operations
– Digital provides the tools
– Exploit automation by linking data pools
– Augment machine data with resource data
– Rapid feedback to mine operations
– Rapid feedforward to downstream
– Overcome resource variability which gives rise to variable downstream performance
– Exploit variability, or make products closer to specifications
University of Adelaide 16
Resource Heterogeneity On-Belt Feed Analysis
Arena, T., & McTiernan, J. (2011). METPLANT 2011 - Metallurgical Plant Design and Operating Strategies.
Feed Variability
17
Drill and geophysical
sensors
Resource Knowledge
Belt Sensors
• Rapid resource knowledge
updating (reconciliation)
• Accurate interpolation of ore
attributes
• Enable rapid decisions on ore
destinations to optimise value
• Enable rapid decisions in
downstream processing
• Enable rapid feedback to mine
operations
• Ore tracking from resource to
mill feed
• Sensor response interpreted in
terms of resource knowledge
• Relative contributions to ore
feeds quantified rapidly
Downstream Decisions
MiningDecisions
Integrated Operations
University of Adelaide 17
LHD and conveyor sensors
Conclusions– Optimisation opportunities exist in mining &
processing
• Fragmentation is key
– Integrated operations seek to link and optimise overall resource value
• Integration by exploiting automation
– Opportunities for research, technology transfer and impact through collaboration
University of Adelaide 18