Enhancing Failure Mode and Effect Analysis with Neutrosophic Inverse Soft Expert Sets

Abstract

In this study, we introduce a novel concept, the Neutrosophic Inverse Soft Expert Set (NISES), and apply it to the Failure Mode and Effect Analysis (FMEA) framework. Developed by NASA, FMEA is a robust tool for addressing industrial challenges. Our approach leverages the Evaluation based on Distance from Average Solution (EDAS) algorithm to solve FMEA problems. We implement this methodology in a real-world scenario involving a steam valve with eight distinct failure modes. Through rigorous analysis, we employ the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to rank the identified failure modes. Comparing our FMEA model, which integrates rough set theory and TOPSIS, with the conventional method, we demonstrate the superior efficiency of our approach. Additionally, we extend the application of Neutrosophic Inverse Soft Expert Sets using the Additive Ratio Assessment-Simplified Version (ARAS-SV) method. This innovative method facilitates a quantitative assessment of alternative options based on multiple attributes, allowing for a precise determination of the optimal choice.

Keywords

• soft set
• inverse soft set
• neutrosophic set
• neutrosophic inverse soft set
• failure mode
• effect analysis
• additive ratio assessment-simplified version method