Digital Twins and the Mining Industry

Abstract

Safe and efficient assimilation of new technologies into current operations in the mining industry requires adapting to new challenges. Traditional mining techniques and operations will inevitably be adjusted to incorporate new methods and machinery. Various industries, from manufacturing and engineering to social sciences, have embraced the Digital Twins (DT) methodology to study complex systems. The benefits of DT, encompassing features like a data hub, simulation and analysis tools, and visualization platforms, are substantial because they replicate their physical counterparts even before their existence. Once the physical twin is constructed, the DT serves as a digital mirror, aiding in ongoing monitoring, improvement, and control. Digital Twins utilize data-driven and physics-based models and advanced analytics to optimize cost, environmental emissions, and resource usage in developing extraction, production, processing, refining, manufacturing, or recycling technologies. They also enable precise control, predictive maintenance, and identification of potential bottlenecks or inefficiencies through simulation, monitoring, and analysis of every step in the supply chain. Utilizing digital twins expedites the development of novel technologies, ensuring their sustainability and competitiveness. Moreover, digital twins could play a role in diversifying commercially viable and environmentally sustainable sources of critical materials, including their recovery from waste streams.