An improved failure mode and effect analysis method for multi-criteria group decision-making in green logistics risk assessment
•This study develops the K-means clustering method to partition the FMEA experts according to their evaluation.•A weight calculation method of FMEA model according to grey correlation coefficient and risk attitude is proposed.•The combination of RT-PROMETHEE II final ranking method is constructed.•A...
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| Vydané v: | Reliability engineering & system safety Ročník 215; s. 107826 |
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| Jazyk: | English |
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Elsevier Ltd
01.11.2021
Elsevier BV |
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| ISSN: | 0951-8320, 1879-0836 |
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| Abstract | •This study develops the K-means clustering method to partition the FMEA experts according to their evaluation.•A weight calculation method of FMEA model according to grey correlation coefficient and risk attitude is proposed.•The combination of RT-PROMETHEE II final ranking method is constructed.•An extended regret theory based on HARA utility function is formed.•Two simulation experiments and comparisons are presented to prove the validity, reliability and superiority of the proposed FMEA model.
As one of the powerful systematic reliability management tool, the failure mode and effect analysis (FMEA) method is adopted to investigate and analyze potential failure mode (FM) risks of the cold chain green logistics (CCGL). Since FMEA experts have different professional backgrounds and risk preferences, they may give evaluation from different angle and emphasis; and express different limited rational behavior. Therefore, this study proposes an improved FMEA model which considers the expert group and the bounded rational behavior of experts. Firstly, this paper develops the K-means clustering method to partition FMEA experts. Further, a calculation model of attribute weights that considers different risk attitudes is proposed. Additionally, this study proposes a combination final ranking method based on regret theory (RT) and PROMETHEE II method. A practical case and two simulation experiments are carried out to demonstrate the validity, reliability and superiority performance of the proposed FMEA model. The improved FMEA model can enhance the fairness and reasonableness of the expert evaluation, improve the adaptability and flexibility of FMEA, and enrich the theoretical research of FMEA method. Findings indicated that it is necessary to consider the grouping and risk attitudes of experts in the practical risk assessment. |
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| AbstractList | As one of the powerful systematic reliability management tool, the failure mode and effect analysis (FMEA) method is adopted to investigate and analyze potential failure mode (FM) risks of the cold chain green logistics (CCGL). Since FMEA experts have different professional backgrounds and risk preferences, they may give evaluation from different angle and emphasis; and express different limited rational behavior. Therefore, this study proposes an improved FMEA model which considers the expert group and the bounded rational behavior of experts. Firstly, this paper develops the K-means clustering method to partition FMEA experts. Further, a calculation model of attribute weights that considers different risk attitudes is proposed. Additionally, this study proposes a combination final ranking method based on regret theory (RT) and PROMETHEE II method. A practical case and two simulation experiments are carried out to demonstrate the validity, reliability and superiority performance of the proposed FMEA model. The improved FMEA model can enhance the fairness and reasonableness of the expert evaluation, improve the adaptability and flexibility of FMEA, and enrich the theoretical research of FMEA method. Findings indicated that it is necessary to consider the grouping and risk attitudes of experts in the practical risk assessment. •This study develops the K-means clustering method to partition the FMEA experts according to their evaluation.•A weight calculation method of FMEA model according to grey correlation coefficient and risk attitude is proposed.•The combination of RT-PROMETHEE II final ranking method is constructed.•An extended regret theory based on HARA utility function is formed.•Two simulation experiments and comparisons are presented to prove the validity, reliability and superiority of the proposed FMEA model. As one of the powerful systematic reliability management tool, the failure mode and effect analysis (FMEA) method is adopted to investigate and analyze potential failure mode (FM) risks of the cold chain green logistics (CCGL). Since FMEA experts have different professional backgrounds and risk preferences, they may give evaluation from different angle and emphasis; and express different limited rational behavior. Therefore, this study proposes an improved FMEA model which considers the expert group and the bounded rational behavior of experts. Firstly, this paper develops the K-means clustering method to partition FMEA experts. Further, a calculation model of attribute weights that considers different risk attitudes is proposed. Additionally, this study proposes a combination final ranking method based on regret theory (RT) and PROMETHEE II method. A practical case and two simulation experiments are carried out to demonstrate the validity, reliability and superiority performance of the proposed FMEA model. The improved FMEA model can enhance the fairness and reasonableness of the expert evaluation, improve the adaptability and flexibility of FMEA, and enrich the theoretical research of FMEA method. Findings indicated that it is necessary to consider the grouping and risk attitudes of experts in the practical risk assessment. |
| ArticleNumber | 107826 |
| Author | Liu, Peide Li, Ying |
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| Keywords | multi-criteria group decision-making cold chain green logistics risk assessment RT-PROMETHEE II failure mode and effect analysis K-means clustering method |
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| SubjectTerms | Adaptability Attitudes Cluster analysis Clustering cold chain green logistics risk assessment Decision analysis Decision making Decision theory Failure analysis failure mode and effect analysis Failure modes K-means clustering method Logistics multi-criteria group decision-making Multiple criterion Reliability analysis Reliability engineering Risk assessment RT-PROMETHEE II Vector quantization |
| Title | An improved failure mode and effect analysis method for multi-criteria group decision-making in green logistics risk assessment |
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