Failure mode and effects analysis integrated with q-rung orthopair fuzzy set theory and multimoora for prioritization of design works in automotive industry

Businesses must ensure continuity by maintaining high-quality standards as competition increases in the automotive industry. The achievement of high-quality standards requires measuring potential error risks and taking action to reduce and eliminate them before transferring them to the customer. At this point, quality risk assessment tools such as failure mode and effect analysis (FMEA) appear. FMEA is a technique that was introduced by the military aviation industry in the 1960s to reduce risks in design studies and improve product safety. The technique aims to determine the ranking of the risks that arise/are likely to arise in the systems with the risk priority number obtained by multiplying the risk factors defined as detectability (D), probability (O), and severity (S). FMEA that is included in the literature as an engineering technique that focuses on design, process, system and service issues and aims to identify and eliminate possible failures, errors and problems before they reach the consumer. In addition, qualitative failure involving subjectivity and related uncertainty, deficiencies in the error definitions of experts, inability to prioritize with the same risk priority number obtained by multiplying different numbers, the slightest change in risk factors significantly affecting the rankings, and the evaluation of risk factors with the same degree of importance are the limitations of traditional FMEA. In this study, to overcome the mentioned limitations of traditional FMEA, the MULTIMOORA method, developed with q-rung orthopair aggregation operators, is proposed as a FMEA method with a new perspective. First, linguistic evaluation information is converted into q-rung orthopair fuzzy numbers to handle the inadequacy and uncertainty of information effectively. Second, expressions defined by linguistic expressions are assigned different priorities using q-rung orthopair fuzzy numbers to solve the problem of the weight of expert and risk factors using by aggregation operators. Finally, the proposed method is aimed to compare the results obtained with other multi-criteria decision-making methods, perform sensitivity analysis and evaluate the proposed approach in terms of its suitability to the FMEA risk analysis method.