Reliability of a k-out-of-n System with Common-cause Failures Using Multivariate Exponential Distribution | Zendy

Tetsushi Yuge | Zendy; Maruyama Megumi | Zendy; Shigeru Yanagi | Zendy

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Reliability of a k-out-of-n System with Common-cause Failures Using Multivariate Exponential Distribution

Author(s) -

Tetsushi Yuge,

Maruyama Megumi,

Shigeru Yanagi

Publication year - 2016

Publication title -

procedia computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.334

H-Index - 76

ISSN - 1877-0509

DOI - 10.1016/j.procs.2016.08.101

Subject(s) - computer science , reliability (semiconductor) , exponential distribution , field (mathematics) , statistics , reliability engineering , reliability theory , exponential function , multivariate statistics , mathematics , failure rate , machine learning , thermodynamics , engineering , pure mathematics , mathematical analysis , power (physics) , physics

In recent years, numerous papers dealing with extensions of Marshall-Olkin distributions have appeared. However, the Marshall- Olkin model is not yet a commonly used mathematical model in the field of risk analysis, even though it has been considered to be suitable for common cause analysis in the field of statistics. We consider the reliability of a k-out-of-n system subjected to Marshall-Olkin type shocks. All combinations of components in the system are assumed to be shock sources in the analysis. We formulate the system reliability and numerically compare the results with those obtained using the conventional α-factor model

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