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Enhanced GO methodology to support failure mode, effects and criticality analysis

Author

Listed:
  • Linlin Liu

    (Beihang University)

  • Dongming Fan

    (Beihang University)

  • Zili Wang

    (Beihang University)

  • Dezhen Yang

    (Beihang University)

  • Jingjing Cui

    (Beihang University)

  • Xinrui Ma

    (Beihang University)

  • Yi Ren

    (Beihang University)

Abstract

Failure mode, effects and criticality analysis (FMECA) is a prerequisite and significant task for reliability analysis of a safety critical complex system; meanwhile, it is complicated, error-prone and time-consuming due to the gap between a dedicated process for system functional design and fault propagation analysis. Moreover, traditional empiricism analysis usually omits potential fault propagations, and the Risk Priority Number cannot display the risk of failure modes that attribute to the entire system effectively and precisely. In this article, GO methodology, a wide-spread intuitive reliability and safety model technique in practical engineering systems, is enhanced to support FMECA in a qualitative and quantitative way. Function operators in the GO model are extended to support the function hierarchy, failure modes definition, parameters, failure computation and the connectivity with other components. Based on the information above, the failure propagation algorithm is presented, utilizing the relationship signified by signal flows in the GO model. Next, depending on the extended GO model and automatic FMEA synthesis algorithm, all of the existent and potential failure effects are obtained automatically without artificial experience. With Bayesian Network, the reliability of the system and the risk assessment of each failure mode are obtained simultaneously. Finally, a case study of a mobile platform of robot is introduced to verify and validates the applicability of the proposed method in reliability analysis domains. The proposed method is compared with conventional FMECA approach. It is shown that the proposed method has a better performance in qualitative FMEA analysis and quantitative analysis in risk assessment and sensitivity analysis.

Suggested Citation

  • Linlin Liu & Dongming Fan & Zili Wang & Dezhen Yang & Jingjing Cui & Xinrui Ma & Yi Ren, 2019. "Enhanced GO methodology to support failure mode, effects and criticality analysis," Journal of Intelligent Manufacturing, Springer, vol. 30(3), pages 1451-1468, March.
    • Handle: RePEc:spr:joinma:v:30:y:2019:i:3:d:10.1007_s10845-017-1336-0
    DOI: 10.1007/s10845-017-1336-0
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    References listed on IDEAS

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    1. Shen, Zupei & Dai, Xingjian & Huang, Xiangrui, 2006. "A supplemental algorithm for the repairable system in the GO methodology," Reliability Engineering and System Safety, Elsevier, vol. 91(8), pages 940-944.
    2. David, Pierre & Idasiak, Vincent & Kratz, Frédéric, 2010. "Reliability study of complex physical systems using SysML," Reliability Engineering and System Safety, Elsevier, vol. 95(4), pages 431-450.
    3. P. Niloofar & M. Ganjali, 2014. "A new multivariate imputation method based on Bayesian networks," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(3), pages 501-518, March.
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    5. Simon Li & Wei Zeng, 2016. "Risk analysis for the supplier selection problem using failure modes and effects analysis (FMEA)," Journal of Intelligent Manufacturing, Springer, vol. 27(6), pages 1309-1321, December.
    6. Hu-Chen Liu & Yi-Zeng Chen & Jian-Xin You & Hui Li, 2016. "Risk evaluation in failure mode and effects analysis using fuzzy digraph and matrix approach," Journal of Intelligent Manufacturing, Springer, vol. 27(4), pages 805-816, August.
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    Cited by:

    1. Khalil Ardeshirtanha & Ahmad Sharafati, 2020. "Assessment of Water Supply Dam Failure Risk: Development of New Stochastic Failure Modes and Effects Analysis," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(5), pages 1827-1841, March.

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