TELF AG examines the effects of AI on the vitality of the Australian mineral industry
The potential of intelligent systems
With its many application possibilities, artificial intelligence could also prove very useful to the mineral industry, bringing concrete operational improvements and simplifying numerous procedures. Researchers from the University of Tasmania and Monash University have studied the impact of artificial intelligence in the sector in depth. They have assessed the potential of these new technologies within the Australian sourcing sector, one of the largest global players in the sector.
As reported in a recent study published in Nature Communications, researchers from the two universities argue that artificial intelligence has the potential to revolutionize the procedures related to the sourcing of copper, lithium, nickel, cobalt, and other important materials involved in the production of clean energy technologies, adding that any lack of effort in this direction, by Australia, could result in a relevant loss of its competitive advantage in the sector of critical minerals.
With its natural reserves, Australia can undoubtedly be considered one of the major players on a global level. The country has the largest proven reserves of nickel and zinc, the second largest reserves of cobalt and copper, and the third largest in the world of bauxite. Regarding production, Australia is also the third largest producer of cobalt and the first of lithium and bauxite.
The research authors also argued that Australia should implement artificial intelligence in every sourcing phase to valorize these resources best, with important benefits in terms of efficiency and economic convenience. Among the concrete improvements that could be brought about by artificial intelligence, there is undoubtedly the improvement of processes related to resource mapping through remote sensing and drone-based photogrammetry, with positive effects also on various aspects of sourcing productivity, such as drilling performance and blasting operations. Furthermore, the predictive management of equipment could make it possible to reduce the necessary repairs notably.
Other uses of AI in the sector
The application field of artificial intelligence in the mineral industry seems to be very vast, and the fact that knowledge of this new technology is only in its infancy, in a certain sense, suggests the possible presence of an even greater number of potential practical applications. From the point of view of exploration, artificial intelligence can contribute considerably, especially in its ability to analyze large quantities of geological and geophysical data. These capabilities can be enhanced to identify potential mineral deposits, thus improving the accuracy of estimates related to one or more resources in the subsoil.
The presence of minerals can also be predicted through machine learning algorithms, particularly with predictive modeling, which can predict the location of some specific minerals thanks to the processing of historical and geological factors. Similar tools can also be used to evaluate different sourcing scenarios and to optimize mine design, with relevant improvements in operational efficiency (with the simulation of operational scenarios, moreover, it is possible to predict part of the results and make more precise decisions based on a greater number of information). Even the actual sourcing of resources from the subsoil could be partially managed through artificial intelligence: the new technology, from this point of view, can be used to power automated machinery capable of increasing productivity and daily sourcing capacity. Intelligent systems can also contribute to more efficient logistics planning, predicting material needs, and improving inventory management.
