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Reliability and risk analysis of large systems with ageing components

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  • KoÅ‚owrocki, K.
  • Kwiatuszewska-Sarnecka, B.

Abstract

Applications of limit reliability functions to the reliability evaluation of large multi-state systems composed of independent components are considered. The main emphasis is on multi-state systems with ageing components because of the importance of such an approach in safety analysis, assessment and prediction, and analysing the effectiveness of operation processes of real technical systems. The results concerned with multi-state series systems are applied to the reliability evaluation and risk function determination of a homogeneous bus transportation system. Results on limit reliability functions of a homogeneous multi-state “m out of n†system are applied to durability evaluation of a steel rope. A non-homogeneous series–parallel pipeline systems composed of several lines of pipe segments is estimated as well. Moreover, the reliability evaluation of the model homogeneous parallel-series electrical energy distribution system is performed.

Suggested Citation

  • KoÅ‚owrocki, K. & Kwiatuszewska-Sarnecka, B., 2008. "Reliability and risk analysis of large systems with ageing components," Reliability Engineering and System Safety, Elsevier, vol. 93(12), pages 1821-1829.
    • Handle: RePEc:eee:reensy:v:93:y:2008:i:12:p:1821-1829
    DOI: 10.1016/j.ress.2008.03.008
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    References listed on IDEAS

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    1. Joseph C. Hudson & Kailash C. Kapur, 1985. "Reliability Bounds for Multistate Systems with Multistate Components," Operations Research, INFORMS, vol. 33(1), pages 153-160, February.
    2. David A. Butler, 1982. "Bounding the Reliability of Multistate Systems," Operations Research, INFORMS, vol. 30(3), pages 530-544, June.
    3. Richard E. Barlow & Alexander S. Wu, 1978. "Coherent Systems with Multi-State Components," Mathematics of Operations Research, INFORMS, vol. 3(4), pages 275-281, November.
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    Cited by:

    1. Funda Iscioglu, 2017. "Dynamic performance evaluation of multi – state systems under non – homogeneous continuous time Markov process degradation using lifetimes in terms of order statistics," Journal of Risk and Reliability, , vol. 231(3), pages 255-264, June.
    2. Li, Y.F. & Peng, R., 2014. "Availability modeling and optimization of dynamic multi-state series–parallel systems with random reconfiguration," Reliability Engineering and System Safety, Elsevier, vol. 127(C), pages 47-57.
    3. Faghih-Roohi, Shahrzad & Xie, Min & Ng, Kien Ming & Yam, Richard C.M., 2014. "Dynamic availability assessment and optimal component design of multi-state weighted k-out-of-n systems," Reliability Engineering and System Safety, Elsevier, vol. 123(C), pages 57-62.
    4. Patelli, Edoardo & Feng, Geng & Coolen, Frank P.A. & Coolen-Maturi, Tahani, 2017. "Simulation methods for system reliability using the survival signature," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 327-337.
    5. Eryilmaz, Serkan & Rıza Bozbulut, Ali, 2014. "An algorithmic approach for the dynamic reliability analysis of non-repairable multi-state weighted k-out-of-n:G system," Reliability Engineering and System Safety, Elsevier, vol. 131(C), pages 61-65.
    6. Xiaogang Song & Zhengjun Zhai & Yangming Guo & Peican Zhu & Jie Han, 2017. "Approximate Analysis of Multi-State Weighted k -Out-of- n Systems Applied to Transmission Lines," Energies, MDPI, vol. 10(11), pages 1-16, October.

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