Predicting Wind Turbine Failures

Get in-time and advanced alerts on potential maintenance issues before they occur and align resources optimally to reduce downtime

Our turnkey enterprise AI solution provides early warning of impending equipment failure weeks before the failure. This helps wind turbine operators minimize equipment downtime, reduce the risk of accidents, and lower maintenance costs while increasing the lifespan of the turbine. Operations and maintenance engineers and technicians at wind turbine operators can now focus on planning maintenance schedules rather than reacting to incidents. Contact us if you're interested in seeing how this solution could work for your business.

Key Metrics


per machine per year

Cost of downtime without AI


per machine per year

Cost of downtime with AI

Wind turbine companies are always looking for ways to improve the reliability and performance of their turbines, as well as reduce the cost of maintaining them over their lifecycle. One key area of focus is the operations and maintenance of the turbines.


By implementing predictive maintenance strategies that use data from the turbines' sensors to identify potential issues before they occur, wind turbine companies can take proactive steps to prevent unplanned downtime and ensure that their turbines are operating at their best. In addition, implementing processes and procedures to ensure that turbines are properly maintained and repaired when needed can help extend their lifespan and improve their overall performance.


AI and machine learning (ML) can play a key role in optimizing wind turbine operations and maintenance. By training an ML model to analyze data from the turbines' sensors and identify patterns or anomalies, wind turbine companies can proactively address potential issues before they become major problems. In addition, ML models can be used to optimize the scheduling and routing of maintenance personnel, helping to ensure that they are able to efficiently and effectively address issues as they arise. By leveraging the power of AI and ML, wind turbine companies can improve the reliability and performance of their turbines, as well as reduce the cost of maintaining them.


  • Extract and prepare data from turbine sensors
  • Build predictive models to forecast maintenance needs based on historical data
  • Get in-time and advanced alerts on potential defects
  • Use optimization techniques to align resources, schedule and workload
  • Access dashboards on turbine performance and reliability
  • Get data driven insights into operations and maintenance

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* Values are approximates arrived at based on earlier experience and/or existing literature. Contact us to find out how you can measure the ROI on this solution for your business