Wind AI Scheduler is an intelligent calendar system that integrates and interprets data from Cognitive’s full suite of offshore wind applications. This approach enables maintenance teams to effortlessly determine the optimal days for conducting repairs, inspections, and upgrades, while also identifying additional work opportunities based on real-time and forecasted accessibility, risk and financial conditions.
Integrated with Cognitive’s ecosystem of advanced tools, Wind AI Scheduler draws on:
WAVES – a vessel-specific forecasting application that determines safe and efficient offshore crew transfer windows based on sea conditions.
Bathymetry – a tidal accessibility planning tool that maps turbine access using site-wide tidal predictions combined with Bathymetric survey data; and
Production Forecaster – an AI-powered model that delivers turbine-specific hourly production forecasts by combining wake modelling, weather forecasts, and energy market pricing.
By pulling and interpreting operational constraints and environmental conditions across all these platforms, Wind AI Scheduler replaces the traditional, spreadsheet-heavy planning process with an intuitive, AI-enhanced experience.
This marks a significant step-change in the industry where, until now, maintenance scheduling has often been time-consuming, fragmented, and disconnected from key operational data.
“Wind AI Scheduler is an industry-first” said Thomas Humphries, CTO at Cognitive Business, speaking about the launch. “It makes future planning seamless for Operations and Maintenance teams by integrating accessibility, safety, and production into a single, intelligent interface. What used to take hours of manual effort and cross-referencing can now be achieved at the click of a button.”
Wind AI Scheduler is currently in development and will integrate Cognitive’s full suite of AI tools, which is already actively supporting operations. The integration of Wind AI Scheduler enables dynamic, data-driven scheduling decisions, optimised resource allocation, improved safety, reduced downtime and minimised production losses.
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