The present study proposes a novel integration of logic tree analysis (LTA) and fuzzy failure mode and effect analysis (Fuzzy-FMEA) in the domain of production machine maintenance planning

Abstract

The reliability and efficiency of machinery in a production system are contingent upon proper failure analysis. The objective of this study is to identify and evaluate the primary failure modes in machine components using the Failure Mode and Effect Analysis (FMEA) method and Risk Priority Number (RPN) calculation. The analysis results indicate that Belt Conveyors and Bearings have the highest RPN value (180), signifying a substantial risk of failure relative to other components. The study identified severity, occurrence, and detection as the primary factors contributing to failure. Additionally, the analysis categorized components based on risk level, with category B (outage) exhibiting a 100% proportion, signifying that all failures have a direct impact on system operations. The findings of this study provide a foundation for the development of a more effective maintenance strategy, aimed at minimizing the likelihood of failure and enhancing the performance of the production system.