Fuzzy FMEA approach with 5S criterion to improve the reliability of apron weigh feeder in a cement plant

This study aimed to develop an innovative methodology that combines Failure Mode and Effects Analysis (FMEA) with Fuzzy logic and the 5S criterion to improve assertiveness in risk management and increase the reliability of apron weigh feeder in the cement industry. The methodological approach included the application of Fuzzy logic to conventional FMEA, using the Fuzzy Logic Toolbox in MATLAB and directly incorporating the 5S criterion into the assessment of criticalities. The study was conducted in a cement plant in Brazil, where failure histories were analyzed by experts to validate the efficiency of the proposal. The results indicated that the integration of 5S with Fuzzy FMEA provided greater sensitivity to operational variables than conventional FMEA, significantly improving decision-making regarding critical failure modes in the studied weigh feeder. The main limitation of this work lies in the dependence of results on the quality of the fuzzy rule base, which must be carefully designed. Future studies could investigate automating fuzzy outputs, integrating predictive maintenance data, and expanding applications to diverse industrial contexts. The proposed methodology is versatile and can be applied across diverse sectors, including healthcare, finance, education and energy, serving as a reference for enhancing risk management and maintenance practices while improving safety, operational efficiency, cost reduction and failure prevention. The work may contribute to more efficient and safer operations, potentially improving workplace safety, reducing the risk of industrial accidents, enhancing the reliability of goods and services delivery and decreasing environmental impacts. This study stands out for its originality in proposing and validating an unprecedented integration of the 5S criterion with FMEA using Fuzzy Logic, filling theoretical gaps and providing a practical approach that can be applied in other industrial contexts.