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Identifying and evaluating enterprise architecture risks using FMEA and fuzzy VIKOR

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  • Hossein Safari

    (University of Tehran)

  • Zahra Faraji

    (University of Tehran)

  • Setareh Majidian

    (University of Tehran)

Abstract

Enterprise architecture (EA) is an approach for managing all components of enterprise and relationships among them. By implementing EA, the organization will be threatened from different aspects. We used failure mode and effect analysis (FMEA) which is a powerful tool for evaluating EA risks. In traditional FMEA, risk priority number (RPN), has been calculated by multiplication of three criteria, severity, occurrence and detection. Because of some drawbacks of the traditional FMEA, this paper—instead of calculating RPN—prioritizes EA risk factors with fuzzy VIKOR. VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje in Serbian, means Multi-criteria Optimization and Compromise Solution) is a multiple attribute decision making technique which aims to rank EA risk factors with respect to the criteria. As regards using linguistic variables, fuzzy approach is used to allow experts to use linguistic variables. The proposed method is used for evaluating twenty EA risk factors, which integrates knowledge and experience acquired from professional experts.

Suggested Citation

  • Hossein Safari & Zahra Faraji & Setareh Majidian, 2016. "Identifying and evaluating enterprise architecture risks using FMEA and fuzzy VIKOR," Journal of Intelligent Manufacturing, Springer, vol. 27(2), pages 475-486, April.
    • Handle: RePEc:spr:joinma:v:27:y:2016:i:2:d:10.1007_s10845-014-0880-0
    DOI: 10.1007/s10845-014-0880-0
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    References listed on IDEAS

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    Cited by:

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    13. Yuan, Jiahai & Li, Xinying & Xu, Chuanbo & Zhao, Changhong & Liu, Yuanxin, 2019. "Investment risk assessment of coal-fired power plants in countries along the Belt and Road initiative based on ANP-Entropy-TODIM method," Energy, Elsevier, vol. 176(C), pages 623-640.
    14. Daniel O. Aikhuele, 2021. "Intuitionistic fuzzy hamming distance model for failure detection in a slewing gear system," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 12(5), pages 884-894, October.
    15. Quan Xiao & Shanshan Wan & Fucai Lu & Shun Li, 2019. "Risk Assessment for Engagement in Sharing Economy of Manufacturing Enterprises: A Matter–Element Extension Based Approach," Sustainability, MDPI, vol. 11(17), pages 1-29, September.
    16. Yi-Jing Zhang & Li-Sheng Hu, 2021. "Fault Propagation Inference Based on a Graph Neural Network for Steam Turbine Systems," Energies, MDPI, vol. 14(2), pages 1-13, January.
    17. Tai-Wu Chang & Huai-Wei Lo & Kai-Ying Chen & James J. H. Liou, 2019. "A Novel FMEA Model Based on Rough BWM and Rough TOPSIS-AL for Risk Assessment," Mathematics, MDPI, vol. 7(10), pages 1-20, September.
    18. Guofeng Ma & Xuhui Pan, 2021. "Research on a Visual Comfort Model Based on Individual Preference in China through Machine Learning Algorithm," Sustainability, MDPI, vol. 13(14), pages 1-23, July.
    19. Moath Alrifaey & Tang Sai Hong & Eris Elianddy Supeni & Azizan As’arry & Chun Kit Ang, 2019. "Identification and Prioritization of Risk Factors in an Electrical Generator Based on the Hybrid FMEA Framework," Energies, MDPI, vol. 12(4), pages 1-22, February.
    20. Xinlong Li & Yan Ran & Genbao Zhang & Yan He, 2020. "A failure mode and risk assessment method based on cloud model," Journal of Intelligent Manufacturing, Springer, vol. 31(6), pages 1339-1352, August.
    21. Amy H. I. Lee & He-Yau Kang & You-Jyun Liou, 2017. "A Hybrid Multiple-Criteria Decision-Making Approach for Photovoltaic Solar Plant Location Selection," Sustainability, MDPI, vol. 9(2), pages 1-21, January.

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