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Reliability analysis of system with timing functional dependency using fuzzy-bathtub failure rates

Author

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  • Mohammad Nadjafi

    (Aerospace Research Institute (Ministry of Science, Research and Technology))

  • Mohammad Ali Farsi

    (Aerospace Research Institute (Ministry of Science, Research and Technology))

Abstract

Dependency among system elements impress the system performance and efficiency, thus dependencies have to be modeled and analyzed. The aim of this paper is introducing and studying a specified dependence in reliability analysis of fault trees with dynamic dependencies; named Timing Functional Dependency (TFDEP) gate. In most systems with functional dependency constructions equipped with known FDEP gate, event failures occur in particular order and their dependencies are only usual and sequentially without any time considerations. However, in some specific systems, the events in addition to the predefined order, are also time-dependent and for each occurrence, a specific event’s activation/deactivation time should be considered. This timing requirement necessitates inventing a new TFDEP gate. On the other hand, in order to exact simulation, the Fuzzy-bathtub distributions are used as the time-to-failure parameter and Fuzzy Monte Carlo technique throughout the predetermined operating time is considered to the simulation process. Finally, the proposed approach is implemented in an air/space system as an application example and the simulation results demonstrated that the presented technique is a valid approach in the analysis of system reliability with timing dependencies and events that have unknown failure occurrence probabilities.

Suggested Citation

  • Mohammad Nadjafi & Mohammad Ali Farsi, 2021. "Reliability analysis of system with timing functional dependency using fuzzy-bathtub failure rates," 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 919-930, October.
  • Handle: RePEc:spr:ijsaem:v:12:y:2021:i:5:d:10.1007_s13198-021-01156-1
    DOI: 10.1007/s13198-021-01156-1
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    References listed on IDEAS

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    1. Xing, Liudong & Shrestha, Akhilesh & Dai, Yuanshun, 2011. "Exact combinatorial reliability analysis of dynamic systems with sequence-dependent failures," Reliability Engineering and System Safety, Elsevier, vol. 96(10), pages 1375-1385.
    2. Zio, E., 2009. "Reliability engineering: Old problems and new challenges," Reliability Engineering and System Safety, Elsevier, vol. 94(2), pages 125-141.
    3. Enrico Zio & Nicola Pedroni, 2010. "Reliability Estimation by Advanced Monte Carlo Simulation," Springer Series in Reliability Engineering, in: Javier Faulin & Angel A. Juan & Sebastián Martorell & José-Emmanuel Ramírez-Márquez (ed.), Simulation Methods for Reliability and Availability of Complex Systems, chapter 0, pages 3-39, Springer.
    4. Marseguerra, M. & Zio, E. & Devooght, J. & Labeau, P.E., 1998. "A concept paper on dynamic reliability via Monte Carlo simulation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 47(2), pages 371-382.
    5. K. Durga Rao & V.V.S. Sanyasi Rao & A. K. Verma & A. Srividya, 2010. "Dynamic Fault Tree Analysis: Simulation Approach," Springer Series in Reliability Engineering, in: Javier Faulin & Angel A. Juan & Sebastián Martorell & José-Emmanuel Ramírez-Márquez (ed.), Simulation Methods for Reliability and Availability of Complex Systems, chapter 0, pages 41-64, Springer.
    6. Marquez, David & Neil, Martin & Fenton, Norman, 2010. "Improved reliability modeling using Bayesian networks and dynamic discretization," Reliability Engineering and System Safety, Elsevier, vol. 95(4), pages 412-425.
    7. Rongxing Duan & Jinghui Fan, 2014. "Reliability Evaluation of Data Communication System Based on Dynamic Fault Tree under Epistemic Uncertainty," Mathematical Problems in Engineering, Hindawi, vol. 2014, pages 1-9, May.
    8. Yuge, T. & Yanagi, S., 2008. "Quantitative analysis of a fault tree with priority AND gates," Reliability Engineering and System Safety, Elsevier, vol. 93(11), pages 1577-1583.
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