Other consortium members are BHP, OZ Minerals, AMIRA International, the Australian Information Industries Association Internet of Things Cluster for Mining and Energy Resources, Australian Semi-conductor Technology Company, Boart Longyear, Consilium Technology, CRC Optimise Resource Extraction, Datanet, Data to Decisions CRC, Eka, Innovyz, Magotteaux, Manta Controls, Maptek, METS Ignited, Mine Vision Systems, Rockwell Automation, the South Australian Chamber of Mines and Energy, SRA IT and Thermo Fisher Scientific Australia.
One of the consortium's first steps will be to establish a secure data room within the university's School of Computer Science with direct data feeds from sensors set up at existing mines. This will allow analysis in real time and comparison with historical data.
Within the first 18 months the consortium aims to justify the capital cost of a system of conveyor belt sensors to allow mass ore sorting.
Another project is to set up a working system of sensors installed in grinding mills to maximise throughput while maintaining product specifications.
South Australia hosts 68% of Australia's economic demonstrated resources of copper and is home to a number of long-life deposits.
University of Adelaide Institute for Mineral and Energy Resources and consortium director Professor Stephen Grano said variability in ore bodies being mined was a key challenge facing the industry.
"We'll be developing advanced technologies to tailor the mining and processing options to the specific characteristics of the mineral ore in real time - an approach known as lean processing," he said.
"The key will be integration of data from when the resource is still in the ground, right through the mining and processing stages.
"We'll be using data analytics and machine learning, enabling the whole system to optimised rather than optimising isolated parts."