Presenting a hybrid approach to risk prioritization based on failure analysis and fuzzy cognitive map: A case study of the automotive parts industry

Increasing competition, the extension of customer expectations and their frequent demand and rapid technological changes have been caused the rapid development of today's manufacturer’s obligations. So that any deficiencies and deviations in the performance of the products lead to loss of manufacturer’s market share. To remove the problems and improve the quality of products, identifying failures must take into consideration. In this study, potential failures are identified by implementing failure modes and effects analysis, with the help of the cross functional team in the car spare parts industry. Then, to achieve results in according to the facts and to remove problem in risk priority number computation, and the identified interrelationships between failures are taken into consideration. Because, the occurrence and control of any failure can affect other failures. In other words, the prioritization of failures based on the fuzzy cognitive map is done with regard to the three criteria including severity, occurrence and detection as well as interrelation between failures. A case study on auto parts manufacturing industry is used to show the abilities of integrating "failure modes and effects analysis-fuzzy cognitive map" for prioritizing failures.