Predictive maintenance
See failures forming before they stop the line.
Machines rarely fail without warning; the signs are in the sensor data, just too subtle to watch by hand. A model that learns each machine's normal behaviour flags the drift early, so maintenance happens on a plan instead of in a panic.
- Collect sensor and telemetry streams plus maintenance logs.
- Learn each machine's normal pattern, then watch for drift.
- Alert with lead time and a likely-cause hint.
- Plan maintenance around the warning, not the breakdown.
- Machine sensor or telemetry data
- Maintenance and breakdown logs
- Run hours and load
- Early warnings with lead time
- Ranked at-risk machines
- Likely-cause hints for the technician
Bottleneck machines where an hour of unplanned downtime is genuinely expensive.
We design and deploy to the ISO/IEC 27001 (information security) and ISO/IEC 42001 (AI management system) frameworks. Data stays where it should, decisions that carry real cost keep a human in the loop, and every model call is logged for audit.
Designed and deployed to these frameworks. Not a certification claim.
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