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Failure mode and effect analysis considering the fairness-oriented consensus of a large group with core-periphery structure

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  • Tang, Ming
  • Liao, Huchang

Abstract

With the increasing complexity of processes and products, and because of the multi-disciplinary and cross-functional nature, a failure mode and effect analysis (FMEA) practice may be implemented in a distributed setting with a large group of FMEA members. In this study, we introduce a large group decision making model for FMEA considering social relationships of FMEA members. Firstly, a group structure detection method is used to reduce the dimension of the large group, which can find a core-periphery structure and a community structure from a meso‑scale perspective. Then, a delegation mechanism is introduced to allocate opinions of periphery FMEA members into those of core FMEA members. Next, we propose a fairness-oriented consensus approach considering a fair distribution of changes in the consensus reaching process. An illustrative example regarding photovoltaic systems is provided to demonstrate the applicability and effectiveness of our proposed model. The key and novel contribution of our paper is to explore how to manage the structure characteristic for FMEA groups under the social network setting. We provide an insight of efficient decision making for complex reliability engineering problems.

Suggested Citation

  • Tang, Ming & Liao, Huchang, 2021. "Failure mode and effect analysis considering the fairness-oriented consensus of a large group with core-periphery structure," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    • Handle: RePEc:eee:reensy:v:215:y:2021:i:c:s0951832021003422
    DOI: 10.1016/j.ress.2021.107821
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    References listed on IDEAS

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    1. Bhattacharyya, S.K. & Cheliyan, A.S., 2019. "Optimization of a subsea production system for cost and reliability using its fault tree model," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 213-219.
    2. Huang, Jia & You, Jian-Xin & Liu, Hu-Chen & Song, Ming-Shun, 2020. "Failure mode and effect analysis improvement: A systematic literature review and future research agenda," Reliability Engineering and System Safety, Elsevier, vol. 199(C).
    3. Zhang, Hengjie & Dong, Yucheng & Xiao, Jing & Chiclana, Francisco & Herrera-Viedma, Enrique, 2021. "Consensus and opinion evolution-based failure mode and effect analysis approach for reliability management in social network and uncertainty contexts," Reliability Engineering and System Safety, Elsevier, vol. 208(C).
    4. Carpitella, Silvia & Certa, Antonella & Izquierdo, Joaquín & La Fata, Concetta Manuela, 2018. "A combined multi-criteria approach to support FMECA analyses: A real-world case," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 394-402.
    5. Tang, Ming & Liao, Huchang, 2021. "From conventional group decision making to large-scale group decision making: What are the challenges and how to meet them in big data era? A state-of-the-art survey," Omega, Elsevier, vol. 100(C).
    6. Lo, Huai-Wei & Liou, James J.H. & Huang, Chun-Nen & Chuang, Yen-Ching, 2019. "A novel failure mode and effect analysis model for machine tool risk analysis," Reliability Engineering and System Safety, Elsevier, vol. 183(C), pages 173-183.
    7. Arash Geramian & Ajith Abraham & Mojtaba Ahmadi Nozari, 2019. "Fuzzy logic-based FMEA robust design: a quantitative approach for robustness against groupthink in group/team decision-making," International Journal of Production Research, Taylor & Francis Journals, vol. 57(5), pages 1331-1344, March.
    8. Dirk Martignoni & Thomas Keil & Markus Lang, 2020. "Focus in Searching Core–Periphery Structures," Organization Science, INFORMS, vol. 31(2), pages 266-286, March.
    9. Héctor H. Guerrero & James R. Bradley, 2013. "Failure Modes and Effects Analysis: An Evaluation of Group versus Individual Performance," Production and Operations Management, Production and Operations Management Society, vol. 22(6), pages 1524-1539, November.
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    Cited by:

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    2. Li, Ying & Liu, Peide & Li, Gang, 2023. "An asymmetric cost consensus based failure mode and effect analysis method with personalized risk attitude information," Reliability Engineering and System Safety, Elsevier, vol. 235(C).

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