A DMAIC Integrated Fuzzy FMEA Model: A Case Study in the Automotive Industry

The growing competitiveness in the automotive industry and strict standards to which it is subject, require high quality standards. For this, tools such as failure mode effects analysis (FMEA) are applied quantify risk of potential modes. However, for qualitative defects with subjectivity associated uncertainty, lack specialized technicians, revealed inefficiency visual inspection process, well limitations FMEA that it. fuzzy set theory allows dealing uncertainty linguistic terms and, together expert systems, modeling knowledge involved tasks human expertise. In response FMEA, a system was proposed. Integrated design, measure, analyze, improve control (DMAIC) cycle, proposed representation improves subjective failures, hardly detected by inspection, compared FMEA. tested real case study at an industrial manufacturing unit. identified modes were analyzed priority number (RPN) resulted, classic RPN. main results several differences between both. classical come from non-linear relationship variables attribution RPN classification assigns results, thus allowing strengthening decision-making regarding mitigation actions most “important”