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 tools that measure texture and grain size upstream, and the real-time geometallurgy models that turn that measurement into an actual circuit-optimization decision on the plant floor.
Key Takeaways Textural analysis, grain size analysis, and mineral mapping run on the same automated-mineralogy and hyperspectral imaging stack: TESCAN TIMA, Zeiss Mineralogic, and Corescan for core-scale hyperspectral work. These platforms increasingly use …
Key Takeaways Crusher circuit optimization is one of the more measurable AI wins on this list: reported gains of 1-5% throughput and 10-15% energy reduction from AI setpoint optimization. Imubit’s Closed Loop AI Optimization uses reinforcement learning to write optimal setpoints directly to …
Key Takeaways Grinding (SAG/ball mills) is one of the single largest energy consumers on a mine site — comminution overall is roughly half of total plant energy use, so small efficiency gains are worth real money. Closed-loop AI controllers now write mill setpoints directly, rather than just …
Key Takeaways “Real-time geometallurgy” is the umbrella term for fusing ore characterization proxies (grind/crush hardness proxies, mineral liberation, %solids) into live setpoint recommendations for the plant, rather than waiting for periodic lab testwork. It runs on the same …