IoT and ML Predictive Maintenance for a 28-Turbine Wind Farm
Challenge
The client is a renewable energy company operating a 28-turbine onshore wind farm in Germany.
Unplanned gearbox and generator failures caused frequent downtime and costly emergency repairs. Scheduled checks and standard SCADA alarms missed early signs of wear, so problems often surfaced only after a turbine had already entered emergency mode.
The client is a renewable energy company operating a 28-turbine onshore wind farm in Germany.
Unplanned gearbox and generator failures caused frequent downtime and costly emergency repairs. Scheduled checks and standard SCADA alarms missed early signs of wear, so problems often surfaced only after a turbine had already entered emergency mode.
Solution
SumatoSoft built a predictive maintenance layer on top of the existing SCADA system. Vibration, temperature, and generator-current data travel through IoT gateways to a cloud pipeline.
Machine learning models learn each turbine's normal behavior and flag wear weeks in advance. Confirmed alerts flow into the client's maintenance planning system through an open API, and engineers use a web dashboard with a fleet map, turbine health summaries, and component-level views.
SumatoSoft built a predictive maintenance layer on top of the existing SCADA system. Vibration, temperature, and generator-current data travel through IoT gateways to a cloud pipeline.
Machine learning models learn each turbine's normal behavior and flag wear weeks in advance. Confirmed alerts flow into the client's maintenance planning system through an open API, and engineers use a web dashboard with a fleet map, turbine health summaries, and component-level views.
Results
- Unplanned downtime down 38%, from 165 to 102 hours per turbine per year
- Fleet availability up from 96.4% to 97.7%
- OPEX reduced by EUR 504,000 across the fleet (22%)
- Average gearbox event cost down from EUR 220,000 to EUR 70,000
- EUR 640,000 investment paid back in 9.8 months
- Unplanned downtime down 38%, from 165 to 102 hours per turbine per year
- Fleet availability up from 96.4% to 97.7%
- OPEX reduced by EUR 504,000 across the fleet (22%)
- Average gearbox event cost down from EUR 220,000 to EUR 70,000
- EUR 640,000 investment paid back in 9.8 months
