A hybrid decision making framework based on fuzzy PIPRECIA-fuzzy EDAS for failure mode and effects analysis

Abstract

The main purpose of the current work is to propose a hybrid multi-criteria decision making (MCDM)-based methodology for the prioritisation of failure modes based on their associated risk levels. In the current work, a novel hybrid MCDM approach, i.e., fuzzy pivot pairwise relative criteria importance assessment (PIPRECIA) integrated with fuzzy evaluation based on distance from average solution (EDAS) has been used to prioritise the different failure modes based on their risk levels. A case study of engine assembly process of tractor is presented to illustrate the demonstration of proposed hybrid MCDM based fuzzy PIPRECIA-fuzzy EDAS methodology. The results obtained by fuzzy PIPRECIA-fuzzy EDAS methodology are validated by the two different hybrid MCDM approaches, i.e., fuzzy PIPRECIA-fuzzy ERVD method and fuzzy PIPRECIA-fuzzy ARAS method. The results obtained by fuzzy PIPRECIA-fuzzy EDAS are quite similar to that obtained by fuzzy PIPRECIA-fuzzy ERVD and fuzzy PIPRECIA-fuzzy ARAS method.