Predictive Maintenance System for European Manufacturing Company
A manufacturing company experienced €1.2M annual losses from unplanned equipment downtime. Custom machine learning models trained on 2 years of sensor data (temperature, vibration, pressure, acoustic) predict equipment failures 48-72 hours in advance. The system integrates with their maintenance scheduling software and sends alerts to technicians. Models are continuously retrained with new data.
- Downtime reduction
- 65%
- Cost savings
- €780K/year
- Prediction accuracy
- 92%
- Maintenance efficiency
- 40%