Optimizing Reachtruck Reliability in Cold Storage Industry Using Reliability Centered Maintenance Based on Fuzzy FMEA

Abstract

Reach trucks are critical equipment in cold storage operations due to their efficiency in lifting and transporting
loads in narrow aisles and cold environments. However, high failure rates and extended downtimes significantly reduce their
reliability, which directly affects operational performance and business revenue. This study aims to optimize the reliability of
reach trucks by identifying critical components and determining the appropriate maintenance intervals using a combined
method of Reliability Centered Maintenance (RCM) and Fuzzy Failure Mode and Effect Analysis (Fuzzy FMEA). The
research employs qualitative and quantitative approaches through failure data analysis, expert judgment, and risk priority
number (RPN) evaluation using fuzzy logic. The hydraulic system and driver unit were identified as the most failure-prone
systems, with the hose and gearbox as the most critical components. The application of fuzzy logic provides a more accurate
prioritization of failure risks compared to conventional FMEA. Furthermore, RCM II was used to develop a preventive
maintenance framework to improve equipment reliability. The findings demonstrate that the integrated approach effectively
reduces downtime and enhances the maintenance planning process. This study contributes to developing a more structured
and risk-based maintenance strategy for reach trucks in the cold storage industry