Multi-state homogeneous Markov models in reliability analysis

https://doi.org/10.1016/0026-2714(80)90011-6Get rights and content

Abstract

In the standard Markov technique applied to reliability analysis, components are characterized by two states: an up state and a down state. The present paper explores the possibility of studying system reliability, by modelling each component with a multi-state homogeneous Markov model (MHMM). It is shown that this approach is of value both in approximating non-exponential probability distributions and in helping to build up suitable models for physical processes. Examples are presented which illustrate how the multi-state technique fits many practical situations. Finally some open problems on this topic are suggested.

References (17)

  • C.L. Proctor et al.

    Microelectron. Reliab.

    (1976)
  • B.S. Dhillon

    Microelectron. Reliab.

    (1976)
  • B.S. Dhillon

    Microelectron. Reliab.

    (1976)
  • B.S. Dhillon

    Microelectron. Reliab.

    (1977)
  • B.S. Dhillon

    Microelectron. Reliab.

    (1977)
  • B.S. Dhillon

    Microelectron. Reliab.

    (1976)
  • M.L. Shooman

    Probabilistic Reliability: An Engineering Approach

    (1968)
  • D.R. Cox et al.

    The Theory of Stochastic Processes

    (1965)
There are more references available in the full text version of this article.

Cited by (11)

  • Markov and semi-Markov models in system reliability

    2022, Engineering Reliability and Risk Assessment
  • A Markov approach to wear-out modelling

    1983, Microelectronics Reliability
  • Approximate method for reliability assessment of complex phased mission systems

    2017, Journal of Shanghai Jiaotong University (Science)
  • A copula-based reliability modeling for nonrepairable multi-state k -out-of-n systems with dependent components

    2016, Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability
View all citing articles on Scopus
View full text