A hybrid decision making framework for modified failure mode effects and criticality analysis

A hybrid model integrating FMEA and HFACS to assess the risk of inter-city bus accidents

The incidence of inter-city bus accidents receives a lot of attention from the public because they often cause heavy casualties. The Human Factors Analysis and Classification System (HFACS) is the prevailing tool used for traffic accident risk assessment. However, it has several shortcomings, for example: (1) it can only identify the potential failure modes, but lacks the capability for quantitative risk assessment; (2) it neglects the severity, occurrence and detection of different failure modes; (3) it is unable to identify the degree of risk and priorities of the failure modes. This study proposes a novel hybrid model to overcome these problems. First, the HFACS is applied to enumerate the failure modes of inter-city bus operation. Second, the Z-number-based best–worst method is used to determine the weights of the risk factors based on the failure mode and effects analysis results. Then, a Z-number-based weighted aggregated sum product Assessment is utilized to calculate the degree of risk of the failure modes and the priorities for improvement. The results of this study determine the top three ranking failure modes, which are personal readiness from pre-conditions for unsafe behavior, human resources from organizational influence, and driver decision-making error from unsafe behavior. Finally, data for inter-city buses in Taiwan in a case study to illustrate the usefulness and effectiveness of the proposed model. In addition, some management implications are provided.

Supply chain sustainability risk decision support model using integrated Preference Selection Index (PSI) method and prospect theory

Purpose

The purpose of this paper is to introduce the integrated model of the Preference Selection Index (PSI) and the prospect theory as new means to appraise the impact of supply chain sustainability risks based on five pillars of sustainability. Research has shown that sustainability risk assessment has a strong positive impact on improving the performance of enterprises.

Design/methodology/approach

This study adopts a new decision support model for assessing supply chain sustainability risk based on additional failure mode and effect analysis parameters and its integration with PSI methodology and prospect theory. A case example of the supply chain small and medium enterprise (SME) producing fashion have been used in this study.

Findings

The result of this study reveals some critical supply chain sustainability risks affecting the sustainability of enterprises under study.

Research limitations/implications

The use of a limited sample is often associated as a limitation in the research studies and this study is based on findings from SMEs in the fashion retail supply chain. This preliminary study provides academics and practitioners an exemplar of supply chain sustainability risk assessment using integration of the PSI method and prospect theory.

Practical implications

The result of this study is beneficial for practitioners, particularly owner–managers of SMEs who can use this study as guidance on how to consider risk behavior to identify and select the critical sustainability risks and plan mitigating strategies accordingly.

Originality/value

Scientific studies on using the PSI and its integration with prospect theory as means to assess the criticality of supply chain sustainability risks is very rare. To the best of the authors’ knowledge, this is the first paper that presents the integrated model of the PSI and prospect theory to rank supply chain sustainability risks based on five pillars of sustainability.

A Failure Mode Assessment Model Based on Neutrosophic Logic for Switched-Mode Power Supply Risk Analysis

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.