@ARTICLE{EDDOUH_Yassine_Maximizing_2024, author={EDDOUH, Yassine and DAYA, Abdelmajid and EL OTMANI, Rabie and TOUACHE, Abdelhamid}, volume={No 1}, journal={Management and Production Engineering Review}, howpublished={online}, year={2024}, publisher={Production Engineering Committee of the Polish Academy of Sciences, Polish Association for Production Management}, abstract={In response to the urgent need for sustainable energy, this study addresses a critical challenge in wind turbine optimization. It focuses on developing a nuanced preventive maintenance strategy to minimize costs and mitigate energy losses. Within this framework, our paper introduces a novel approach employing a Monte Carlo simulation to identify the optimal preventive maintenance frequency, striking a balance between cost efficiency and energy loss mitigation. The results show, that grouped maintenance approach, pinpointing an optimal frequency of 93 months. This strategic configuration minimizes costs to \$9997 while concurrently maintaining an average energy loss of 32.014 MWh, resulting in a notable 4.29% increase in total energy production. Variability analysis reveals that increasing maintenance frequency reduces cost fluctuations, while energy loss remains relatively stable. These findings elucidate the interplay among preventive maintenance strategies, cost, and reliability in the realm of wind turbine performance optimization}, title={Maximizing Wind Turbine Efficiency: Monte Carlo Simulation Based on Cost and Energy Loss Analysis for Optimal Preventive Maintenance}, URL={http://www.czasopisma.pan.pl/Content/131007/PDF-MASTER/998_2k.pdf}, doi={10.24425/mper.2024.149994}, keywords={wind turbine, preventive maintenance, Optimization, Monte Carlo, Reliability, Production process}, }