Manufacturing & Industrial
Smart Factory IoT
$3.2M
Saved in year one
94%
Prediction accuracy
Challenge
Unplanned line stops were expensive; maintenance ran mostly on fixed intervals, missing early failure signals buried in vibration and temperature noise.
Solution
Ingestion pipeline from PLCs and sensors into a time-series warehouse, feature engineering for asset families, and gradient-boosted models with human-readable explanations for floor teams.
Results
- 72% reduction in unplanned downtime on equipped lines.
- Maintenance shifted from calendar-based to condition-based with clear work-order integration.
Azure IoT
Python
TimescaleDB
Grafana
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