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Nonparametric predictive inference for reliability of a k-out-of-m:G system with multiple component types

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  • Aboalkhair, Ahmad M.
  • Coolen, Frank P.A.
  • MacPhee, Iain M.

Abstract

Nonparametric predictive inference for system reliability has recently been presented, with specific focus on k-out-of-m:G systems. The reliability of systems is quantified by lower and upper probabilities of system functioning, given binary test results on components, taking uncertainty about component functioning and indeterminacy due to limited test information explicitly into account. Thus far, systems considered were series configurations of subsystems, with each subsystem i a ki-out-of-mi:G system which consisted of only one type of components. Key results are briefly summarized in this paper, and as an important generalization new results are presented for a single k-out-of-m:G system consisting of components of multiple types. The important aspects of redundancy and diversity for such systems are discussed.

Suggested Citation

  • Aboalkhair, Ahmad M. & Coolen, Frank P.A. & MacPhee, Iain M., 2014. "Nonparametric predictive inference for reliability of a k-out-of-m:G system with multiple component types," Reliability Engineering and System Safety, Elsevier, vol. 131(C), pages 298-304.
  • Handle: RePEc:eee:reensy:v:131:y:2014:i:c:p:298-304
    DOI: 10.1016/j.ress.2014.04.010
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    References listed on IDEAS

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    1. Zio, E., 2009. "Reliability engineering: Old problems and new challenges," Reliability Engineering and System Safety, Elsevier, vol. 94(2), pages 125-141.
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    Cited by:

    1. Hajipour, Yassin & Taghipour, Sharareh, 2016. "Non-periodic inspection optimization of multi-component and k-out-of-m systems," Reliability Engineering and System Safety, Elsevier, vol. 156(C), pages 228-243.

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