AI-Driven Mineral Sorting Systems
AI-Driven Mineral Sorting Systems use computer vision, advanced sensors, and optimization models to identify, classify, and separate ore with high precision throughout the mining value chain. By optimizing mineral phase transformations, beneficiation, and crushing parameters in real time, they increase metal recovery, reduce energy and reagent consumption, and lower operating costs while improving plant throughput and product quality.
The Problem
“Your plant is burning energy and losing metal because it can’t see ore in real time”
Organizations face these key challenges:
Recovery drops whenever ore characteristics change and no one notices until it hits the monthly report
Operators constantly retune crushers, mills, and flotation lines by trial and error
Energy and reagent consumption creep up with no clear root cause or real-time visibility
Product quality and throughput swing shift-to-shift, depending on who is on the control room desk
Lab assays arrive hours or days late, so process changes are always reactive, never proactive
Impact When Solved
Technologies
Technologies commonly used in AI-Driven Mineral Sorting Systems implementations:
Key Players
Companies actively working on AI-Driven Mineral Sorting Systems solutions: