14 February 2017: General Manager – Stakeholder Engagement, Clytie Dangar, reports on a recent engagement between QUT and CRC ORE which started with a two-day a week secondment to the CRC ORE offices and resulted in identification of a tangible application for their work in the field.
|Dr Suriadi Suriadi and Sander Leemans working closely with Nick Beaton|
This article was published in CRC ORE News - February 2017
Collaboration in action
What does it mean to collaborate? The Merriam-Webster dictionary defines collaboration as;
to work jointly with others or together especially in an intellectual endeavor
to cooperate with an agency or instrumentality with which one is not immediately connected
to cooperate with or willingly assist an enemy of one's country and especially an occupying force
We certainly hope the third definition does not apply at CRC ORE!
Our mission at CRC ORE is to provide a fertile environment where collaboration is actively fostered between our participants and staff working on real life issues for the mining industry.
A great example of collaboration in action at CRC ORE is the recent engagement between QUT and CRC ORE. CRC ORE encourages participants to consider sending staff or students to spend some time at the CRC ORE office at Pullenvale so they can be fully absorbed into the day-to-day activities and actively contribute to discussions.
A number of meetings between QUT researchers and CRC ORE members took place between September and November 2016 to agree on how Program 4 (in which QUT researchers are actively involved) can fruitfully collaborate with Program 3. QUT’s role in Program 4 involves the application and extension of machine learning, statistics, process analytics, and process automation techniques to improve mining operations. From these meetings, it was clear that data analytics expertise of the QUT team can be used to deliver additional functionality to the IES software from Program 3.
Two QUT staff members who work full-time on Program 4 from the Information Systems School and School of Mathematical Sciences, Dr Suriadi Suriadi and Dr Sander Leemans, agreed to base themselves for, on average, two days per week at CRC ORE from October 2016. By regularly spending time at the CRC ORE office, they were actively exposed to implementation and research projects already underway at CRC ORE. At the same time, it also allowed for CRC ORE staff to be learning from and interacting with Suriadi and Sander on a daily basis.
Under the guidance of the academic co-leaders (Prof. Kevin Burrage, Prof. Arthur ter Hofstede) and a chief investigator (Dr Moe Wynn), Suriadi and Sander worked closely with CRC ORE members on developing a first stage roadmap for the application of advanced data analytics to streamline operational processes in hard rock metal mining. The QUT team has a wealth of experience in successfully conducting similar work within other industries, such as healthcare, insurance, and climate modelling. It is expected that this can be strategically applied to the mining industry to improve its operations. To this end, a good understanding of the mining industry is needed to identify opportunities for real and effective applications for their work in the context of a mining operation.
Suriadi says that within this project, they will need to analyse data collected from ore processing plants which are different from business activities data that QUT normally deal with. “By working closely with domain experts from CRC ORE, we have been able to quickly make sense of the data and identify opportunities where our experiences in the application of data analytics in other industries can be used to improve mining operations,” he says.
Through close collaboration with CRC ORE colleagues, it was collectively recognised that there was a tangible application for their work in the field. In particular, by working closely with Nick Beaton, CRC ORE’s General Manager IES and Program 3 Coordinator, this initial collaboration led to the development of a formal research project proposal for the development of high fidelity simulation process models, a validated Integrated Analysis Method (IAM), and an initial assessment of a novel dynamic forecasting model to allow better process control strategies in the mining process.
This proposal was approved for funding by the Centre Funded Project Committee in early February. It is a great example of the value of active collaboration delivering tangible outcomes for both CRC ORE and QUT.