"Vibration analysis AI predicts turbine failures 14 days in advance, cutting downtime costs by $280k/year per unit."
Renewable Energy
4 months development
6 AI specialists
Wind turbine operators faced massive financial losses from unexpected equipment failures. Traditional maintenance schedules were reactive, leading to catastrophic breakdowns that cost $280,000-$500,000 per incident in repairs and lost energy production.
Key challenges included:
We developed an AI-powered predictive maintenance system that analyzes vibration patterns, temperature fluctuations, and performance metrics to predict failures weeks in advance.
FFT-based anomaly detection
LSTM networks for time series
Temperature, pressure, acoustic
Precise failure time prediction
24/7 data collection and analysis
Instant notifications to maintenance teams
Automated spare parts ordering
Maintenance scheduling optimization
Subscription model for energy providers
Discover how our predictive maintenance AI can revolutionize your renewable energy infrastructure and deliver massive cost savings.