All Solutions
Predictive Maintenance
Detect equipment failures before they happen using machine data and AI.
The Problem
Unexpected equipment failures cause costly unplanned downtime and emergency repairs. Scheduled maintenance intervals are either too frequent (waste) or too infrequent (failure).
Our Approach
Machine learning models trained on real-time MACHHUB sensor data — vibration, temperature, current, pressure — that detect abnormal patterns indicating imminent failure, triggering maintenance work orders before the asset breaks.
Expected Outcome
Reduce unplanned breakdowns by up to 50%, optimize maintenance intervals, and extend asset life through condition-based intervention.
What's Included
- Real-time vibration, temperature, current, and pressure monitoring via MACHHUB
- Anomaly detection using machine learning models
- Remaining Useful Life (RUL) estimation per asset
- Predictive alert routing to maintenance team
- Automatic work order generation on threshold breach
- Model retraining as new failure data is captured
Ready to implement Predictive Maintenance?
Our team will assess your current setup and propose the right approach for your operation.