A neutrosophic MCDM framework for prioritizing preventive and detection actions in automotive manufacturing

Abstract

The quality and reliability of the production process in the automotive industry can significantly affect the market reputation and overall business performance of the entire company. In this paper, a Multi-Criteria Decision-Making (MCDM) model is defined for determining the priority of preventive and detection actions, i.e., a guideline that can be used to follow the prioritization of these actions. To model uncertainty and imprecision in expert evaluations, the model integrates Single-Valued Neutrosophic Sets (SVNSs) with the Single-Valued Neutrosophic Weighted Averaging Operator (SVNWAO) and the ELimination Et Choix Traduisant la REalité (ELECTRE) method. SVNWAO is used for determining the weights of criteria, while ELECTRE is applied for ranking the considered actions. The proposed methodology is applied in a case study conducted in a company that is a tier-1 supplier in the automotive industry. In cooperation with company experts, a total of 12 specific management actions and 6 criteria were identified according to which these actions were evaluated. The research results showed that Poka-Yoke by design is the most reliable action, providing long-term efficiency, followed by Update of standardized work instructions, Additional operator training, and Increased inspection frequency. The proposed model, as well as the results of this research, provide practitioners with a robust and objective tool for prioritizing actions, as well as for allocating resources in a complex and dynamic industrial environment.