Abstract
Reducing the potential risks in the manufacturing process to improve the reliability of the switched-mode power supply (SMPS) is a critical issue for the users’ safety. This paper proposes a novel failure mode and effects analysis (FMEA) model based on hybrid multiple criteria decision-making (MCDM), which adopts neutrosophic set theory into the proposed model. A developed neutrosophic Best Worst method (NBWM) is used to evaluate the weights of risk factors and determine their importance. Secondly, the neutrosophic Weight Aggregated Sum Product Assessments (NWASPAS) method is utilized to calculate the Risk Priority Number (RPN) of the failure modes. The proposed model improves the shortcomings of traditional FMEA and improves the practical applicability and effectiveness of the Best Worst method (BWM) and Weight Aggregated Sum Product Assessments (WASPAS) methods. In addition, this study uses neutrosophic logic to reflect the true judgments of experts in the assessment, which considers authenticity, deviation, and uncertainty to obtain more reliable information. Finally, an empirical case study from an SMPS company headquartered in Taiwan demonstrates the effectiveness and robustness of the proposed model. In addition, by comparing with two other FMEA models, the results show that the proposed model can more clearly reflect the true and effective risks in the assessment. The results can effectively help power supply manufacturers to assess risk factors and determine key failure modes.
Highlights
In today’s highly competitive consumer electronics industry environment, cumulative sales of many hot-selling products have reached tens of millions of units [1]
Worst method (BWM) and Rough Technique for Order Preference by Similarity to an Ideal Solution (R-TOPSIS) to obtain the ranking of failure modes. They used a multinational audio equipment manufacturing company to demonstrate that the model effectively overcomes many shortcomings of traditional failure mode and effects analysis (FMEA), helping decision-makers and Research and Design (R&D) departments improve product reliability
Many academic articles point out that the FMEA model combined with fuzzy theory can improve the accuracy of risk analysis
Summary
In today’s highly competitive consumer electronics industry environment, cumulative sales of many hot-selling products have reached tens of millions of units [1]. To consider user behavior under complex circumstances such as risk and uncertainty, studies have been developing machine learning algorithms to learn and predict complex scenarios to improve the quality of service for users [5,6] Another commonly used method in the field of risk management is FMEA. Worst method (BWM) and Rough Technique for Order Preference by Similarity to an Ideal Solution (R-TOPSIS) to obtain the ranking of failure modes They used a multinational audio equipment manufacturing company to demonstrate that the model effectively overcomes many shortcomings of traditional FMEA, helping decision-makers and Research and Design (R&D) departments improve product reliability. This paper proposes a novel FMEA model based on hybrid MCDM, which adopts neutrosophic set theory into the model This theory can consider the uncertainty of the evaluation environment, and explore the true judgments of experts during the evaluation (the measured factors include truth, falsity, and indeterminacy).
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