Evaluating risks of sustainable supply chain by the failure mode and effect analysis method in fuzzy environment (case study: Saba battery)

Despite the numerous benefits of globalization and the emergence of advanced technologies, they have put the sustainable supply chain in subject to the social, economic, environmental risks. The aim of this study is to develop a new approach to identify and prioritize the risks involved in sustainable supply chain by using the failure mode and effect analysis (FMEA) technique. In this way, the fuzzy sets theory is applied to calculate the risk priority numbers with regard to the fuzzy importance coefficients of risk factors including probability of occurrence, severity and detectability for each risk factor. However, proposed approaches have a computational inefficiency in ranking the fuzzy priority numbers. The fuzzy weighted geometric mean and linear programming model is used in a different way to determine the fuzzy risk priority numbers and then the fuzzy preference relations is applied to compare these numbers for prioritizing sustainability risk factors. Risk factors of the sustainable supply chain in the battery industry are identified and then prioritized by the cross-functional team by using the proposed method. The results show that the approach is capable to provide similar results than other ones with a high computational performance.