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Fault tree analysis based on TOPSIS and triangular fuzzy number

Author

Listed:
  • Hongping Wang

    (Southwest University)

  • Xi Lu

    (Southwest University)

  • Yuxian Du

    (Southwest University)

  • Chenwei Zhang

    (Southwest University)

  • Rehan Sadiq

    (University of British Columbia Okanagan)

  • Yong Deng

    (Southwest University
    Northwestern Polytechnical University)

Abstract

Fault tree analysis (FTA) is widely used in the failure probability evaluation of a system. The conventional failure probabilities of basic events are treated as crisp values. However, in many real applications, it is often difficult to evaluate failure probabilities of basic events from past occurrences. In order to address this issue, a new FTA method based on the technique for order preference by similarity to an ideal solution and the triangular fuzzy number is presented. Compared with the existing method, our proposed method is more efficient with less complexity.

Suggested Citation

  • Hongping Wang & Xi Lu & Yuxian Du & Chenwei Zhang & Rehan Sadiq & Yong Deng, 2017. "Fault tree analysis based on TOPSIS and triangular fuzzy number," 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. 8(4), pages 2064-2070, December.
  • Handle: RePEc:spr:ijsaem:v:8:y:2017:i:4:d:10.1007_s13198-014-0323-5
    DOI: 10.1007/s13198-014-0323-5
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    References listed on IDEAS

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    3. Volkanovski, Andrija & ÄŒepin, Marko & Mavko, Borut, 2009. "Application of the fault tree analysis for assessment of power system reliability," Reliability Engineering and System Safety, Elsevier, vol. 94(6), pages 1116-1127.
    4. Chang, Da-Yong, 1996. "Applications of the extent analysis method on fuzzy AHP," European Journal of Operational Research, Elsevier, vol. 95(3), pages 649-655, December.
    5. Wei, Daijun & Deng, Xinyang & Zhang, Xiaoge & Deng, Yong & Mahadevan, Sankaran, 2013. "Identifying influential nodes in weighted networks based on evidence theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(10), pages 2564-2575.
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    Cited by:

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    3. Hsin-Chieh Wu & Horng-Ren Tsai & Tin-Chih Toly Chen & Keng-Wei Hsu, 2021. "Energy-Efficient Production Planning Using a Two-Stage Fuzzy Approach," Mathematics, MDPI, vol. 9(10), pages 1-17, May.

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