This is like putting a very smart autopilot into rock crushers and mineral processing lines. The AI continuously watches how the equipment is running and how the ore behaves, then automatically tweaks settings to get more metal out of the same rock while using less energy and wearing out parts more slowly.
Mining companies lose money and energy when crushing and processing lines are not tuned perfectly: variable ore hardness, operator differences, unplanned downtime, and inefficient energy use reduce throughput and recovery. Integrating AI into Metso’s equipment aims to keep the process constantly optimized, improving throughput, recovery, and equipment lifetime while reducing energy consumption and unscheduled stops.
Tight coupling of AI with proprietary mineral processing equipment, control systems, and decades of process know‑how and sensor data, creating a feedback loop competitors cannot easily replicate.
Hybrid
Time-Series DB
High (Custom Models/Infra)
Real-time inference at the edge in harsh mine environments (latency, connectivity, hardware constraints) and the need for site-specific model calibration across highly variable ore bodies.
Early Majority
Integration of AI directly into OEM crushing and mineral processing equipment, rather than as a bolt-on analytics layer, enabling real-time closed-loop control and optimization tailored to specific machines and flowsheets.