Investigation and Classification of Failure Modes with Weighted Assessment using Various Fuzzy Logic Techniques

In the recent scenario, medium-scale automobile industries face daily challenges to maintain maximum quality and reliability amid multiple production procedures and limited available resources. This research presents a cohesive framework using various optimization techniques such as Fuzzy Failure Mode and Effects Analysis (FFMEA), Fuzzy Decision-Making Trial and Evaluation Laboratory (FDEMATEL), Fuzzy Analytic Hierarchy Process (FAHP), and Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS) to analyze failure mode rankings within production environments. In this case study, a medium–scale automobile industry is evaluated using a proposed model to identify failures, such as raw material delivery delays and limited supplier support. Results indicate that the cohesive fuzzy Multi-Criteria Decision-Making (MCDM) framework yields effective outcomes for reducing failures. Therefore, our proposed framework serves as a reliable tool for making informed decisions to optimize resource allocation in automobile manufacturing.