<![CDATA[This study applies the Fuzzy Failure Mode and Effects Analysis (Fuzzy FMEA) method to identify, evaluate, and prioritize potential failures in the rice milling production process at Mas Nun’s facility. A total of 14 failure modes were identified based on primary data collected through direct observation, interviews, and literature review. The traditional Risk Priority Number (RPN) was calculated using severity, occurrence, and detection scores, and then refined through fuzzy logic modeling implemented in MATLAB R2022a using the Mamdani inference method. The results show that machine malfunction represents the highest risk with an RPN of 567 and a Fuzzy Risk Priority Number (FRPN) of 827. Additional high-priority failures include high moisture content in rice, poor grain quality, and inadequate drying processes. The fuzzy approach significantly enhances risk prioritization by handling linguistic uncertainty and producing more nuanced FRPN rankings. The study also integrates the 5W+1H framework to propose structured preventive and corrective actions. These findings underscore the relevance of Fuzzy FMEA in agro-industrial settings, particularly for small and medium enterprises (SMEs), by enabling more accurate risk assessment and improving production quality control.]]>
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