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Mastering Digital Twins: real-world cases from offshore experts

The Masterclass Digital Twin, hosted by Fieldlab Zephyros in collaboration with the Offshore For Sure partnership, brought together innovators, researchers, and industry leaders to explore how virtual models are reshaping offshore renewable energy. From predictive wind turbine maintenance to immersive training environments, the sessions showcased practical applications already making offshore operations smarter, safer, and more efficient.

Offshore For Sure (O4S) | 19/09/2025

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Opening Remarks

The workshop opened with Ferry Visser (Fieldlab Zephyros, WCM) and Peter Scheijgrond (Bluespring), who highlighted the crucial role of digital innovation in accelerating offshore renewable energy. They underlined how Digital Twins can bring certainty to unpredictable marine environments, reduce risks for technology developers, and create momentum for collaboration across industry and research. Their remarks set an engaging and forward-looking tone for the workshop that followed.

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Introduction to Digital Twins

Charlotte Larmuseau from HOWEST provided an approachable introduction to Digital Twins, explaining how these virtual replicas help bridge the gap between simulation and real-world operation. She stressed the need for reliable data to drive insight and predictive value, demonstrating how virtual engineering boosts production and logistics.

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Predictive Wind Turbine Blade Maintenance

Feike Savenije from TNO presented the development of a digital twin designed to predict and prevent wind turbine blade failures. Using simulation models, machine learning, and operational data, this initiative aims to move maintenance from reactive to proactive, reducing costs and preventing downtime.

SCADA data to optimize future tidal stream power projects

Jeremy Smith from Tocardo demonstrated how six years of SCADA data was used to create and validate digital twins for tidal turbines. By integrating real-time monitoring and predictive analytics, Tocardo improved performance, planned maintenance more efficiently, and gained valuable insights—even identifying issues before they happened.

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