Journal ArticleA Safety‐Aware Framework for Offshore Wind Turbine MaintenanceHaensch, Anna [Data Science Institute University of Wisconsin‐Madison Madison Wisconsin USA]; Tronci, Eleonora M [Department of Civil and Urban Engineering, Center for Urban Science and Progress New York University New York City New York USA] (ORCID:0000000346091078); Banerjee, Aidan [Tufts Institute for Artificial Intelligence Tufts University Medford Massachusetts USA]; Valencia, Veronica [Department of Bioengineering Northeastern University Boston Massachusetts USA]; Moaveni, Babak [Department of Civil and Environmental Engineering Tufts University Medford Massachusetts USA]In this paper, we suggest a framework for determining the best operation and maintenance strategies for offshore wind turbines. The framework takes into account both quantitative and qualitative data gathered from the wind turbines. The proposed framework consists of a simulation‐optimization approach for designing, planning, and scheduling maintenance operations for offshore wind farms and finding the optimal intervention solution for minimizing costs while keeping a high availability of wind turbines and guaranteeing safety standards for workers. Several parameters and constraints are addressed to account for the realistic complexity of the problem, such as weather conditions, resource cost, and maintenance duration. A numerical case study focusing on offshore wind turbine blade maintenance is presented to demonstrate the implementation of the proposed framework. The example simulates realistic defect progression scenarios, stratified by severity level, and incorporates empirically grounded estimates of failure rates, repair costs, technician requirements, and vessel logistics. The study illustrates how the simulation‐optimization approach integrates economic considerations, resource constraints, and safety risk factors to support data‐informed maintenance scheduling decisions under uncertainty.</p>Wiley2025-12-0110662995Wind Energy28121095-4244https://doi.org/10.1002/we.700652230630National Science Foundation