Integrasi FMEA–Logic Tree Analysis–RCM untuk Prioritisasi Kegagalan dan Penentuan Strategi Pemeliharaan Berbasis Data pada Multi Mover M600U

Purpose: This study aims to identify critical failure modes and develop a structured, data-driven maintenance strategy for the Multi Mover M600U heavy equipment at PT XYZ. Previous studies generally applied FMEA and RCM separately, leaving the transition from risk identification to maintenance task selection insufficiently connected, particularly for heavy equipment in the metallurgical industry. Methodology: The study integrates Failure Mode and Effects Analysis (FMEA) to evaluate failure severity, occurrence, and detection; Logic Tree Analysis (LTA) to assess failure criticality and consequences; and RCM-based task selection to determine appropriate maintenance actions, using three months (January–March 2023) of operational and breakdown data from Multi Mover M600U. Results: The highest Risk Priority Number (RPN) was 350, found in the Electrical PLC component, with a total RPN of 777 for the Electrical and Brake system, identifying it as the largest contributor to downtime. The Electrical PLC is recommended for Time Directed (TD) and Failure Finding (FF) tasks, while the Chamber Brake, Pneumatic Relay, and Solenoid are addressed through Condition Directed (CD) and Failure Finding (FF) approaches. Conclusion: The proposed risk-based maintenance prioritization strategy reduces the likelihood of unexpected downtime and provides a systematic basis for maintenance planning on Multi Mover M600U. Originality: The main contribution of this study is an integrated FMEA–LTA–RCM analytical framework based on operational data that explicitly links risk prioritization to maintenance task selection for heavy equipment in the metallurgical industry — an integration not systematically addressed in prior research.