A curated, evidence-based library of publicly available AI implementations and inspiration cases across the mining value chain
Browse real-world cases. Refine by goal, data, equipment, or commodity.
55 cases
How BHP achieved $5.5M in annual savings through predictive maintenance for haul trucks
ML models trained on failure modes and telemetry prioritized risk-based maintenance. That cut unplanned failures and safely extended intervals.
How Vale avoided $7.8M in losses through predictive maintenance on rotating equipment
Always-on vibration and process analytics flag emerging faults. Early fixes prevent breakdowns and production loss.
How Rio Tinto reduced lost production time by up to 94% through predictive analytics
Cross-site models anticipate downtime drivers and trigger prevention. Teams recover hours that previously disappeared.
How BHP reduced haulage costs by 20% with autonomous fleet at WAIO operations
Centralized autonomous dispatch delivered 89% availability and consistent cycle times across expanding iron ore operations.
How Rio Tinto achieved 15% cost reduction through autonomous haul trucks in the Pilbara
Komatsu AHS smoothed haul cycles and reduced idle time, delivering 700 additional hours per truck annually with zero safety incidents.
How a North American coal mine reduced haulage costs by 20% with Komatsu FrontRunner AHS
Integrated autonomous dispatch balanced loading and reduced queuing, delivering 30% better fleet utilization.
How leading mining companies reduced fatigue incidents through AI-based operator monitoring
In-cab cameras track eyelids and head pose to flag fatigue and distraction for timely supervisor action. Sites reported ~50% fewer fatigue alarms.
How St Barbara (Touquoy) increased grade by ~7% through 3D blast-movement modelling
OREPro3D predicts ore displacement and updates dig lines. Less dilution and better classification improve feed quality.
How Fortescue achieved 30%+ productivity increase through autonomous fleet transformation
Cat MineStar Command coordinated 168 autonomous trucks across multiple sites, moving 1.4 billion tonnes with consistent performance.
How Seeing Machines / Caterpillar cut fatigue events by up to 90% through eye-tracking
Camera analytics detect microsleeps and distraction in real time. Sites reported 7090% reductions in fatigue-related events.
How Boliden Aitik / Epiroc improved drilling productivity through autonomous blasthole drilling
Row-by-row autonomy standardizes quality and reduces exposure. Sites report higher utilization and consistent holes.
How Fosterville Gold Mine / ABB cut ventilation energy costs through Level-4 VoD automation
Tracking and sensors tune airflow by zone as people and machines move. This lowers energy while maintaining safe air quality underground.
How industry operators increased comminution throughput through AI-enhanced APC
Models optimize mill and crusher setpoints in real time. Variability falls and specific energy improves.
How research teams improved blast design through rock-mass classification from MWD
Supervised ML turns pressure/torque/RPM into geotech classes. Better inputs cut overbreak/underbreak and downstream losses.
How academic teams lowered ventilation energy through AI-based process control
Controllers predict gas levels and pre-emptively adjust fans and doors. Energy drops while safety margins stay intact.
How academic/industry teams stabilized flotation through video-based froth prediction
Deep learning forecasts froth states seconds ahead, letting APC tune setpoints earlier. Operations become steadier with higher recovery.
How Glencore George Fisher Mine boosted productivity through autonomous underground loaders/trucks
AutoMine phases from tele-remote to full automation across stopes. Continuous operation improves safety and utilization.
How industry mines cut ventilation energy through demand-based control
Tracking and sensors match air to activity in real time. Energy falls while air quality standards are maintained.
How KoBold Metals accelerated discoveries through ML-driven exploration targeting
Models fuse geochem, geophysics and remote sensing to rank prospectivity. Drilling focuses on higher-probability zones, reducing time and cost.
How multiple operators increased haulage consistency through Komatsu autonomous haulage
AHS integrates GNSS, radar and dispatch for 24/7 cycles. Fleets accumulate 100k+ autonomous hours with fewer interactions.
How Razor Labs (IMARC examples) improved fleet utilization through predictive maintenance
RUL and failure-risk models guide interventions on trucks and shovels. Fewer catastrophic failures keep fleets moving.
How SLDM (Santa Luz) improved dilution control through predictive blast-movement modelling
Pre/post-blast modelling sharpens polygon decisions. Teams route material with more confidence and less variability.
How XMPro (various mines) raised truck availability through asset health monitoring
Condition indicators and anomaly scores surface engine, hydraulic and drive issues early. Maintenance shifts from reactive to planned.
How BHP reduced outages through risk-based predictive maintenance
Models focus attention on high-risk failure modes, extending PM intervals. The result is fewer unexpected stoppages.