<![CDATA[Reach trucks are critical equipment in cold storage operations due to their efficiency in lifting and transportingloads in narrow aisles and cold environments. However, high failure rates and extended downtimes significantly reduce theirreliability, which directly affects operational performance and business revenue. This study aims to optimize the reliability ofreach trucks by identifying critical components and determining the appropriate maintenance intervals using a combinedmethod of Reliability Centered Maintenance (RCM) and Fuzzy Failure Mode and Effect Analysis (Fuzzy FMEA). Theresearch employs qualitative and quantitative approaches through failure data analysis, expert judgment, and risk prioritynumber (RPN) evaluation using fuzzy logic. The hydraulic system and driver unit were identified as the most failure-pronesystems, with the hose and gearbox as the most critical components. The application of fuzzy logic provides a more accurateprioritization of failure risks compared to conventional FMEA. Furthermore, RCM II was used to develop a preventivemaintenance framework to improve equipment reliability. The findings demonstrate that the integrated approach effectivelyreduces downtime and enhances the maintenance planning process. This study contributes to developing a more structuredand risk-based maintenance strategy for reach trucks in the cold storage industry]]>
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