Evaluating the risk of failure modes with a hybrid MCDM model under interval-valued intuitionistic fuzzy environments

- A hybrid MCDM model is proposed in this study for improving FMEA.
- The uncertainty and vagueness of assessment information are handled by IVIFSs.
- Risk factor weights are calculated by using the IVIF-ANP method.
- Failure modes are ranked by using the IVIF-COPRAS method.
- The proposed FMEA can obtain a more accurate risk priority of failure modes.

Failure mode and effect analysis (FMEA) is a prospective risk assessment technique broadly used in various industries for enhancing the safety and reliability of systems, products, processes and services. Nonetheless, when the traditional FMEA is applied in actual situations, it exposes some important insufficiencies, especially in the evaluation of failure modes, the weighting of risk factors, and the ranking of failure modes. Therefore, in this paper, a new FMEA model which integrates COmplex PRoportional ASsessment (COPRAS) and analytic network process (ANP) method is proposed to assess and rank the risk of failure modes under interval-valued intuitionistic fuzzy context. The proposed risk priority approach combines the advantages of interval-valued intuitionistic fuzzy sets (IVIFSs) in coping with uncertainty, vagueness and incompleteness, and the merits of COPRAS and ANP in solving multi-criteria decision making problems. Finally, a practical case in hospital service setting is presented to illustrate the accuracy, effectiveness and flexibility of the proposed model.