With the goal of keeping miners safer and boosting operational efficiency, the University of Queensland and research collaborator Plotlogic have developed a new technology for identifying and classifying minerals at the mine face, in real time, using artificial intelligence (AI).
Ross McAree, head of the UQ School of Mechanical and Mining Engineering, said the mapping scans can be performed at every stage of the mining process using hyperspectral imaging. The capability to identify ore grade immediately could play a large role in future autonomous mining systems, and at this point can help a user develop a mine plan before digging.
The university’s research work was supported by the Minerals Research Institute of Western Australia (MRIWA). MRIWA said real-time ore grade classification at the mine face could offer a significant benefit to large-scale efficient operations such as enhanced mine scheduling; improved resource recovery and minimised processing waste; and the support of autonomous mining systems and machinery.
Grant funding for the research totalled A$485,000. MRIWA contributed A$250,000 to the work.