<![CDATA[The spot welding process using robotic systems is associated with a high risk of failure, including spot weld release, spatter, missed welds, unavailable weld spots, missing brackets, porous welds, double welds, incorrect weld positions, and sliding joint parts. This study aims to enhance risk assessment in spot welding by integrating fuzzy logic inference with Failure Mode and Effects Analysis (FMEA) to overcome the limitations of conventional FMEA in handling uncertainty and ambiguity. The proposed model incorporates fuzzy representations of severity, occurrence, and detection parameters to calculate the Fuzzy Risk Priority Number (FRPN) through three stages: fuzzification, fuzzy inference, and defuzzification. A case study was conducted in the spot welding process of automotive body components in Karawang, using real process data and expert validation. The results show that FRPN values range from 3.95 to 6.38, with the highest risks identified in spot weld release (FRPN = 6.38) and incorrect weld position (FRPN = 6.29), indicating that these failure modes are the top priorities for corrective actions. Furthermore, the fuzzy FMEA approach provides better discrimination of risk levels compared to conventional FMEA, particularly in differentiating failure modes with similar RPN values, thereby improving the accuracy and reliability of risk prioritization.]]>
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