Ranking manufacturing processes from the quality management perspective in the automotive industry

The aim of this study is to propose a fuzzy decision-making model to rank manufacturing processes from the quality management perspective in the automotive industry. This paper proposes a model for improving quality management through the assessment and ranking of manufacturing subprocesses with respect to key performance indicators (KPIs). The developed model, supported with the fuzzy extended ELECTRE III, allows for the determination of subprocesses' rank. An illustrative example indicates that the proposed model could be very useful in everyday business operations as total quality management asset. The model can handle all uncertain and vague input data by applying the theory of fuzzy sets. The research also suggests different managerial implications because it provides an adequate tool for overall quality improvement. The number of treated KPIs is relatively high, so ELECTRE III method gives an advantage over other multicriteria analysis methods because it embraces less subjective thinking and demands slightly less experts' knowledge during the process of decision making and assessment.