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  • Improving productivity
    though innovation

    Improving operational value and reversing the marked trend of declining productivity
  • New ways to identify
    and nurture innovation

    Technology development and implementation for the global minerals industry
  • User-driven
    partnership model

    Collaborations between technology developers, commercial suppliers and end users
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The Cooperative Research Centre for Optimising Resource Extraction (CRC ORE) is founded under the Cooperative Research Centres program.

CRC Business AusGov Industry reverse

The Centre is supported by AMC Consultants, AMIRA, Anglo American, AngloGold Ashanti, Bear Rock Solutions, BHP, Comet Strategy, CRC Mining, CSIRO, Curtin, DataMine Australia, Gekko Systems, Glencore, Hatch, IMDEX, JKTech, Magotteaux, METS Ignited, METSO, Mipac, MRIWA, Newcrest, NRC Canada, OreControl Blasting Consultants, Orica, Queensland University of Technology (QUT), Scantech, Sodern, Split Engineering, SRK Consulting Canada, Sumitomo, Teck, University of Adelaide, University of Queensland (UQ), University of Tasmania (UTAS) and Whittle Consulting.

MINING Participants (implementation)

Anglo American
AngloGold Ashanti
BHP Billiton

METS Participants (delivery)

METS Ignited

METS Associates: AMC Consultants, Bear Rock Solutions, Comet Strategy, DataMine Australia, Gekko Systems, Magotteaux, Mipac, OreControl Blasting Consultants, Scantech, Split Engineering, SRK Consulting Canada, Whittle Consulting

RESEARCH Participants

Curtin University
Mining3 (formerly CRC Mining)

NRC Canada
The University of Adelaide
The University of Queensland

27 May 2019: Growing up in Kuala Lumpur Malaysia, Edwin Koh always knew he wanted to be an engineer, but had no idea his journey would lead him to work in mining research in Brisbane, Australia.

Following the final year of his Chemical Engineering degree, Edwin participated in the 2018 Cooperative Research Centre for Optimising Resource Extraction (CRC ORE) Summer Vacation Program. Edwin_Koh_-_resize.jpgEdwin Koh

During the program he assessed the application of machine leaning techniques in process modelling. A neural network was trained to simulate a comminution circuit using open source neural network training environments such as TensorFlow. The objective of this project was to use these new methodologies to improve process simulations and predictions in CRC ORE’s Integrated Extraction Simulator (IES).

“As a student it was exciting to apply my learning to examine the feasibility of using machine learning to improve daily simulation predictions in minerals processing models,” Edwin said.

Soon after completing the Summer Vacation Program, the talented pianist and occasional basketball player was invited back to CRC ORE as an employee to continue this work in a part time capacity as a data analyst.

Edwin noted that predictor models were historically individually tailored for mine sites and not necessarily applicable to the wider industry.

“We assumed there had to be a better technique for prediction of daily process performance, and now we are able to explore how machine learning can be used in the mining industry” he said.

“Machine learning methods can be used to assist operators and mine and process planners to analyse a large amount of data and solve complex problems that involve numerous variables.”

At CRC ORE, Edwin is being mentored by Dr. Eiman Amini, Senior Metallurgical and Process Control Engineer. Together they are working to harness the power of machine learning for the benefit of the mining industry.

Eiman is pleased by the thought processes his young mentee brings to the role.

“Edwin is young and sharp and brings a host of ideas that aren’t traditionally used in the mining and metallurgy industry.  Edwin would like to assess and apply new methodologies that have been successfully implemented in other industries.” Eiman said.

Eiman commented that CRC ORE aims to deliver improved accuracy and precision of predictions for mining operations by enabling constant learning from the process data, meaning operators can rely on their software to adapt as it goes along.

“In simple terms, we are helping systems locate hidden patterns relevant to local conditions,” he said.

“Machine learning is a good solution, for now, but we also have our eye on what might be beneficial for the industry beyond this current technology,” Edwin said.

While at CRC ORE, Edwin is furthering his study, working towards a postgraduate doctoral degree in ‘Machine Learning in Minerals Processing’. His PhD will take approximately three years to complete, in which time he is looking to gain further hands on experience in the mining industry at CRC ORE and beyond.

Read about our 2018 Summer Vacation Students here.



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