Failure Mode and Effects Analysis Based on Z-Numbers and the Graded Mean Integration Representation

被引:2
|
作者
Zhang, Hanhan [1 ]
Xu, Zhihui [2 ]
Qian, Hong [1 ]
Su, Xiaoyan [1 ]
机构
[1] Shanghai Univ Elect Power, Sch Automat Engn, Shanghai 200090, Peoples R China
[2] State Key Lab Nucl Power Safety Monitorig Technol, Shenzhen 518172, Peoples R China
来源
基金
上海市自然科学基金;
关键词
Safety assessment; FMEA; risk priority number; Z-number; the graded mean integration representation; RISK-EVALUATION;
D O I
10.32604/cmes.2022.021898
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Failure mode and effects analysis (FMEA) is a widely used safety assessment method in many fields. Z-number was previously applied in FMEA since it can take both possibility and reliability of information into consideration. However, the use of fuzzy weighted mean to integrate Z-valuations may have some drawbacks and is not suitable for some situations. In this paper, an improved method is proposed based on Z-numbers and the graded mean integration representation (GMIR) to deal with the uncertain information in FMEA. First, Z-numbers are constructed based on the evaluations of risk factors O, S, D for each failure mode by different experts. Second, weights of the three risk factors and experts are determined. Third, the integration representations of Z-numbers are obtained by a new method based on the GMIR method. Finally, risk priorities of the failure modes are derived considering the weights of experts and risk factors. Two examples and a case study are given to show the use of the proposed method and comparison with other methods. The results show that the proposed method is more reasonable, universal and simple in calculation.
引用
收藏
页码:1005 / 1019
页数:15
相关论文
共 50 条
  • [1] Failure Mode and Effects Analysis based on Z-numbers
    Jiang, Wen
    Xie, Chunhe
    Wei, Boya
    Tang, Yongchuan
    INTELLIGENT AUTOMATION AND SOFT COMPUTING, 2018, 24 (01): : 165 - 172
  • [2] Risk Prioritization in Failure Mode and Effects Analysis with Extended SWARA and MOORA Methods Based on Z-Numbers Theory
    Ghoushchi, Saeid Jafarzadeh
    Gharibi, Kazhal
    Osgooei, Elnaz
    Ab Rahman, Mohd Nizam
    Khazaeili, Mohammad
    INFORMATICA, 2021, 32 (01) : 41 - 67
  • [3] Z*-numbers: Augmented Z-numbers for machine-subjectivity representation
    Banerjee, Romi
    Pal, Sankar K.
    INFORMATION SCIENCES, 2015, 323 : 143 - 178
  • [4] A hybrid generalized TODIM based risk prioritization method for failure mode and effect analysis with linguistic Z-numbers
    Hu, Limei
    JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2023, 44 (05) : 7935 - 7955
  • [5] Failure mode and effect analysis using VIKOR method based on interval-valued linguistic Z-numbers
    Fan, Jianping
    Zhu, Qianwei
    Wu, Meiqin
    JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2024, 46 (01) : 1183 - 1199
  • [6] A New Model for Failure Mode and Effect Analysis Integrating Linguistic Z-Numbers and Projection Method
    Huang, Jia
    Xu, Dong-Hui
    Liu, Hu-Chen
    Song, Ming-Shun
    IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2021, 29 (03) : 530 - 538
  • [7] On Ranking of Continuous Z-Numbers with Generalized Centroids and Optimization Problems Based on Z-Numbers
    Qiu, Dong
    Xing, Yumei
    Dong, Rongwen
    INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS, 2018, 33 (01) : 3 - 14
  • [8] A Fuzzy Sliding-Mode Control Based on Z-Numbers and LAMDA
    Morales, L.
    Aguilar, J.
    Rosales, A.
    Pozo-Espin, D.
    IEEE ACCESS, 2021, 9 : 117714 - 117733
  • [9] Decisions Ranking Based On Z-Numbers
    Banasik, Arkadiusz
    Lawnik, Marcin
    EDUCATION EXCELLENCE AND INNOVATION MANAGEMENT: A 2025 VISION TO SUSTAIN ECONOMIC DEVELOPMENT DURING GLOBAL CHALLENGES, 2020, : 12271 - 12280
  • [10] Approximate reasoning based on similarity of Z-numbers
    Aliev, R. A.
    Pedrycz, W.
    Huseynov, O. H.
    Aliyev, R. R.
    Guirimov, B. G.
    IRANIAN JOURNAL OF FUZZY SYSTEMS, 2024, 21 (01): : 159 - 172