<![CDATA[The effectiveness of the maintenance strategy highly influences the availability of the crane barge offshore system. This study aims to quantitatively optimize the availability of the crane barge offshore system by identifying failure patterns, determining critical subsystems that contribute most to downtime, and formulating an optimal maintenance strategy through the integration of Reliability-Centered Maintenance (RCM), Failure Mode and Effects Analysis (FMEA), and Pareto analysis combined with probabilistic distribution approaches. Data were obtained from 14 failure events over six months, covering time between failures (TBF) and time to repair (TTR). The analysis revealed that the Hydraulic System and Running Gear subsystems are the dominant contributors to downtime. The Weibull distribution was selected to model the failures, yielding a Mean Time Between Failures (MTBF) of 267.53 hours and a Mean Time to Repair (MTTR) of 7.19 hours. Simulation results showed that system availability could reach 97.66% with maintenance based on optimal time intervals. Dynamic reliability calculations demonstrated significant differences compared to conventional average-based methods, highlighting the importance of statistical approaches in determining preventive maintenance intervals. This approach provides a quantitative foundation for developing adaptive, proactive, and data-driven maintenance strategies, with broad potential applications for similar industrial equipment.]]>
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