Sulzer Schmid boosts wind turbine maintenance efficiency with AI-powered anomaly detection

Sulzer Schmid, a leader in energy services, has transformed wind turbine rotor blade inspections with an AI-driven solution. Using autonomous drones and a cloud-based platform, the company automated and enhanced blade image acquisition and analysis, delivering faster, more accurate results for wind asset owners. The 3DX Blade Platform integrates Microsoft Azure and Power BI, consolidating inspection data and surfacing insights through intuitive dashboards. By implementing Azure Machine Learning Studio with AutoML, Sulzer Schmid automated machine learning model building, improving detection precision and operational speed. The solution identifies over 99% of critical blade damages automatically, drastically reducing manual review workloads. Future advancements include AI-driven damage classification and repair recommendations, supported by continuous data collection and Microsoft’s expert guidance. The partnership with Microsoft provides Sulzer Schmid with ongoing access to AI specialists and support as part of the Microsoft for Startups Program, ensuring the inspection technology stays at the cutting edge. Additionally, in-house blade experts review AI results, guaranteeing data quality and accuracy. The solution aims to optimize maintenance planning, minimize turbine downtime, and maximize renewable energy production, setting a new standard for rotor blade inspection efficiency.