prioritizing of manufacturing supply chain failures by integrated decision making approach based on bwm and copras under z-information

Failure mode and effect analysis (fmea) is a proactive step-by-step approach to identify and prioritize potential failures in manufacturing supply chain. it is a method that enhances safety and customer satisfaction by preventing flaws. conventional fmea has drawbacks that has been improved by various researches over time. one way to make fmea more efficient is to use mcdm techniques in order to better ranking. in this paper, we propose a new risk evaluation fmea model, which applies the zbwm and z-copras to determine risk factors’ weight and prioritize failure modes. first, the fmea team identifies the failure modes and rpn elements values (s, o, d, e and t). also, in this phase the reliability of each identified failure modes is determined. then, the fuzzy weights of quintuple factors are calculated by zbwm. finally, the failure states are ranked based on fuzzy values and considering reliability by z-copras. the performance of the new approach is tested in automobile industry. the results indicate that using z-copras method has impressive effect on improving the effectiveness of the conventional fmea.