Concentrate handling, smelting and refining is a smaller AI-adoption category on this site so far, covering AI-assisted chemical analysis of concentrate composition and the transport and shipping logistics of getting concentrate from mine to smelter. Both are …
Crushing and grinding is a comminution-circuit optimization problem at its core: predicting how ore texture and grain size will behave through the circuit, then using that to tune crushing and grinding setpoints in real time rather than on a fixed schedule. This category covers the image-analysis …
Drilling and blasting generate a stream of sensor data - measurement-while-drilling logs, blast-hole probe readings, hydrogeologic monitoring feeds - that AI increasingly processes in real time rather than after the fact. This covers autonomous and AI-assisted …
Exploration and target generation is where most day-one AI adoption happens in mining, because the data - drill core, geochemistry, geophysics surveys - already exists in the volumes machine learning needs. This is the instrument layer: automated mineralogy platforms like TIMA, MLA and QEMSCAN, …
Flotation is one of the most mature applications of industrial AI in mineral processing: closed-loop reinforcement-learning controllers like Imubit already write setpoints directly to plant control systems rather than just recommending them to an operator. This category covers that closed-loop …
Geological modelling and resource estimation is where AI assists a geologist’s interpretation rather than replacing it: implicit modelling software that infers lithology, structure and alteration from sparse drill data, and statistical models that …
Geometallurgy characterization turns hyperspectral and mineralogical data into the proxy models a block model actually runs on: clay content, alteration proxies, and recovery and hardness predictions - so the metallurgical response of a deposit can be estimated ahead of mining rather than discovered …
Grade control and geotechnical control are mostly a pattern-recognition problem applied to data an operation already collects: advanced sensing (XRF, XRD, LIBS, hyperspectral) calibrated against known grade, automated ore sampling, and bench slope stability …
Marketing, costs and reconciliation covers the commercial side of a mining operation: AI-assisted production forecasting for the marketing and sales function that has to sell what the mine actually produces, reconciled against what the geological and mine-planning models predicted. This is the …
Mine planning and blast design increasingly run on AI-assisted optimization rather than manual iteration: platforms that generate and evaluate blast designs and blasting sequences, and evolutionary search over long-term production schedules. This category …