Risk Evaluation in Failure Mode and Effects Analysis Based on D Numbers Theory

被引:1
|
作者
Liu, B. [1 ,2 ]
Deng, Y. [1 ]
机构
[1] Univ Elect Sci & Technol China, Inst Fundamental & Frontier Sci, Chengdu 610054, Sichuan, Peoples R China
[2] Sun Yat Sen Univ, Sch Data & Comp Sci, Guangzhou, Guangdong, Peoples R China
基金
中国国家自然科学基金;
关键词
failure mode and effects analysis; Dempster-Shafer evidence theory; D numbers; risk evaluation; aggregate assessment; EVIDENTIAL REASONING APPROACH; POWER AGGREGATION OPERATOR; FUZZY-SETS; RELIABILITY; FMEA; SYSTEM; UNCERTAINTY; ATTRIBUTES; ENTROPY;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Failure mode and effects analysis (FMEA) is a useful technology for identifying the potential faults or errors in system, and simultaneously preventing them from occurring. In FMEA, risk evaluation is a vital procedure. Many methods are proposed to address this issue but they have some deficiencies, such as the complex calculation and two adjacent evaluation ratings being considered to be mutually exclusive. Aiming at these problems, in this paper, A novel method to risk evaluation based on D numbers theory is proposed. In the proposed method, for one thing, the assessments of each failure mode are aggregated through D numbers theory. For another, the combination usage of risk priority number (RPN) and the risk coefficient newly defined not only achieve less computation complexity compared with other methods, but also overcome the shortcomings of classical RPN. Furthermore, a numerical example is illustrated to demonstrate the effectiveness and superiority of the proposed method.
引用
收藏
页码:672 / 691
页数:20
相关论文
共 50 条
  • [31] An improved failure mode and effects analysis method based on uncertainty measure in the evidence theory
    Wu, Dongdong
    Tang, Yongchuan
    QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL, 2020, 36 (05) : 1786 - 1807
  • [32] Manufacturing Execution System Risk Analysis Based on an Improved Failure Mode and Effects Analysis Method
    You J.
    Deng Q.
    Deng, Qingwen (dengqingwen502@163.com), 1600, Science Press (48): : 132 - 138
  • [33] Evaluation of Healthcare Failure Mode And Effect Analysis For Risk Assessment
    Harry, T.
    Manger, R.
    Cervino, L.
    Pawlicki, T.
    MEDICAL PHYSICS, 2016, 43 (06) : 3519 - 3519
  • [34] Evaluation of physical risk factors by fuzzy failure mode and effects analysis: an apparel mill example
    Demir, Erhan
    Sabir, Emel Ceyhun
    INTERNATIONAL JOURNAL OF OCCUPATIONAL SAFETY AND ERGONOMICS, 2024,
  • [35] Risk evaluation in failure mode and effects analysis with extended VIKOR method under fuzzy environment
    Liu, Hu-Chen
    Liu, Long
    Liu, Nan
    Mao, Ling-Xiang
    EXPERT SYSTEMS WITH APPLICATIONS, 2012, 39 (17) : 12926 - 12934
  • [36] Development of a Failure Mode and Effects Analysis Based Risk Assessment Tool for Information Security
    Lai, Lotto Kim Hung
    Chin, Kwai Sang
    INDUSTRIAL ENGINEERING AND MANAGEMENT SYSTEMS, 2014, 13 (01): : 87 - 100
  • [37] Risk prioritization in failure mode and effects analysis under uncertainty
    Zhang, Zaifang
    Chu, Xuening
    EXPERT SYSTEMS WITH APPLICATIONS, 2011, 38 (01) : 206 - 214
  • [38] Failure mode and effects analysis to reduce risk of heparin use
    Pino, Felicity A.
    Weidemann, Darcy K.
    Schroeder, Lisa L.
    Pabst, Damon B.
    Kennedy, Audrey R.
    AMERICAN JOURNAL OF HEALTH-SYSTEM PHARMACY, 2019, 76 (23) : 1972 - 1979
  • [39] Knowledge Based Training Derived from Risk Evaluation Concerning Failure Mode, Effects and Criticality Analysis in Autonomous Railway Systems
    Gnauer, Clemens
    Prochazka, Andrea
    Szalai, Elke
    Chlup, Sebastian
    Luimpoeck, Sabrina
    Fraunschiel, Anton
    Schmittner, Christoph
    2021 5TH INTERNATIONAL CONFERENCE ON SYSTEM RELIABILITY AND SAFETY (ICSRS 2021), 2021, : 47 - 52
  • [40] A new risk prioritization model for failure mode and effects analysis
    Anes, V.
    Henriques, E.
    Freitas, M.
    Reis, L.
    QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL, 2018, 34 (04) : 516 - 528