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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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