Mining & Heavy Industry
Predict failures, prevent hot-event stoppages, and raise tons/hour with explainable, closed-loop actions across mixed fleets.
Common challenges
Industry pain points
- Haul-road bottlenecks; pit entry/exit slow-downs.
- Hot tire/engine events and unplanned stops.
- Shift-change spikes; fatigue-related anomalies.
- Mixed telemetry vendors and siloed dashboards.
+5%
Tons / hr
-30%
Unscheduled stops
+11%
Availability
Hot-event trend (placeholder)
Data fabric
Signals we ingest
- Fleet CAN telemetry (engine load/temp, pressure, RPM).
- Payload cycles, tire temps/pressures, haul speeds.
- Geofences, camera/ADS detections, queueing time.
Connect & deploy
- OPC UA, REST, MQTT; cloud or ruggedized edge.
- Explainable alerts for safety & maintenance review.
Closed-loop ops
Actions & automations
- Slow-zone & reroute automations by slope/condition risk.
- Maintenance dispatch on predicted hot events.
- Charge/fuel windows by shift & utilization.
- Pit-entry throttling to prevent queue spikes.
Explainability example
Unplanned stop risk (haul 3→crusher). Why: tire temp ↑, engine load ↑, slope > threshold, queue at shovel. Action: slow-zone + reroute + tech dispatch.
Saliency bars (placeholder)
Modeled impact
Business impact
- Higher production stability and fewer hot-event halts.
- Longer tire/engine life; fewer emergency repairs.
- Safer operations with auditable context.
+4–8%
Tons/hr
-20–35%
Stops
-15%
Hot events
Live simulation (illustrative)
92.3%
Avail.
18
Active trucks
3
Active alerts
Risk index trend (placeholder)