Ranking Failure Modes with Pythagorean Fuzzy Rough VIKOR: A Case Study in Automatic Washing Machines

Abstract

Failure mode and effects analysis (FMEA) is known for its remarkable and exceptional ability to recognize , evaluate, and remove possible failure modes in various industrial applications. It offers a broad point of view for scrutinizing possible failures, their roots, and their consequences in processes, manufactured articles, and designs. The conventional FMEA method has faced significant criticism due to its difficulties in accurately determining the weight of risk factors, recognizing the priority of failure modes, and handling vagueness during risk assessment. A new linguistic assessment model called Pythagorean fuzzy rough VIKOR is introduced to address these shortcomings. This model utilizes a combination of Pythagorean fuzzy numbers and rough information to improve the accuracy and effectiveness of risk assessment. We also apply the suggested VIKOR method to identify the less or more severe problems. Before applying the VIKOR method, we find criteria weights using the Pythagorean fuzzy rough entropy method. The importance of our proposed method has been discussed in the case study of an automatic washing machine. Different comparison studies show that the Pythagorean fuzzy rough method effectively addresses subjectivity and uncertainty when evaluating failure modes. This paper provides evidence to support using the Pythagorean fuzzy rough VIKOR (PFR-VIKOR) technique for ranking failure modes. This approach has demonstrated exceptional benefits in dealing with subjective and uncertain factors during the evaluation process.