An industrial IoT platform that continuously monitors machine vibration, temperature, and acoustic signatures to predict equipment failure days in advance.
The challenge
Factories run 24/7 — unplanned downtime costs thousands per hour. Existing maintenance schedules waste resources on healthy machines while missing critical failures.
The approach
Deployed edge-mounted sensor arrays feeding a real-time ML pipeline. The system learns each machine's baseline behavior and flags anomalies with confidence scores, pushing alerts to operators before thresholds are breached.
94%
Failure prediction accuracy
-73%
Unplanned downtime
3.2x
ROI in first year