Crushing & Grinding on Eigenform AI Geo Tooltips

AI Image Analysis for Ore Texture, Grain Size and Mineral Mapping

Mon, 21 Sep 2026 00:00:00 +0800

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 CNN-based classifiers rather than fixed spectral lookup tables to resolve grain boundaries and mixed-pixel mineralogy.
Output feeds two downstream uses directly: comminution/liberation modeling (how finely you need to grind to liberate value minerals) and geometallurgical domaining.
This is a mature, commercially deployed capability (ai_relevant: Yes across all three) — not a research prototype.
Malvern Panalytical’s Morphologi line is a relevant alternative specifically for particle-scale grain-size distribution work outside the SEM-based platforms.

TL;DR

Run polished samples or drill core through an automated SEM mineralogy platform (TIMA, Mineralogic) or hyperspectral core scanner (Corescan) to get quantitative texture, grain-size, and mineral-map data with built-in ML-based classification, rather than manual petrographic description.

Crushing

Mon, 21 Sep 2026 00:00:00 +0800

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 control systems in real time, rather than relying on a static linearized process model.
ABB Ability for Mining is the more established alternative, though it depends more on linearized process models that can struggle with the genuinely non-linear behavior of crushing circuits.
Marked “Yes” — this is a production capability with measured results at deployed sites, not a lab demo.

TL;DR

Optimize your crusher circuit with closed-loop AI control — Imubit uses reinforcement learning to continuously adjust setpoints against live plant data, reporting real throughput and energy gains over traditional control approaches like ABB Ability.

Grinding

Mon, 21 Sep 2026 00:00:00 +0800

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 advising an operator, using deep neural networks trained on historical plant data instead of a first-principles model.
Vendors report 2-5% throughput gains, lower specific energy, fewer liner strikes/shutdowns, and better downstream recovery from AI-driven grinding control.
This is a mature, commercially available category — not an emerging research idea — with multiple named vendors actively selling into mining today.

TL;DR

You do AI-assisted grinding mostly by adopting a closed-loop advanced process control (APC) platform — ABB Ability Expert Optimizer, Imubit’s Closed Loop AI Optimization, or Metso’s control stack built on the MillSense charge sensor — that learns your mill’s behavior from historical data and continuously adjusts feed rate, water addition, and mill speed in real time.

Real Time Geometallurgy

Mon, 21 Sep 2026 00:00:00 +0800

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 closed-loop AI platforms used for crushing/grinding optimization — this is an application pattern, not a separate piece of software.
The core idea: instead of running a static geomet model built from quarterly composite samples, you stream ore-property predictions into the control room as material actually arrives at the plant.
This is commercially available today via general-purpose industrial AI/APC vendors, not a mining-specific off-the-shelf product — expect a systems-integration project, not a shrink-wrapped purchase.

TL;DR

Real-time geometallurgy means piping your ore characterization proxies (hardness, liberation, clay content, %solids) into a closed-loop AI/soft-sensor platform like Imubit or ABB Ability for Mining so the plant adjusts itself to the ore in front of it, instead of running on a fixed setpoint tuned for average ore.