• DocumentCode
    2665486
  • Title

    Reliability analysis of multi-state systems with s-dependent components

  • Author

    Dao, Cuong D. ; Zuo, Ming J.

  • Author_Institution
    Dept. of Mech. Eng., Univ. of Alberta, Edmonton, AB, Canada
  • fYear
    2015
  • fDate
    26-29 Jan. 2015
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    The assumption of stochastic independence between components is frequently made in studies of system reliability. However, in a specific system, the failure of a component can trigger the failure of other components, or the current health condition of a component may affect the performance of other components. Thus, the state of a component can affect the state and degradation of other components in a multi-component system, that is, stochastic dependence (s-dependence) may exist in real and complex systems. In this paper, reliability analysis of multi-state systems (MSS) with s-dependent components will be considered. The MSS consists of 2 multi-state components in series, with each component possibly operating at different performance levels, varying from perfect functioning to complete failure. When the first component degrades to a lower performance level, it affects the state as well as the degradation of the other component in the system. A combined technique of stochastic process and modified universal generating function is used to evaluate the system reliability. The combined approach is then verified using the Monte Carlo Simulation method. An illustrative example on reliability analysis of MSS with dependent components is also provided.
  • Keywords
    Monte Carlo methods; condition monitoring; failure analysis; reliability theory; stochastic processes; MSS; Monte Carlo simulation method; S-dependent components; complete failure; component degradation; component failure; component state; health condition; modified universal generating function; multicomponent system; multistate components; multistate systems; perfect functioning; performance levels; reliability analysis; stochastic independence; stochastic process; system reliability; Degradation; Markov processes; Mathematical model; Monte Carlo methods; Probability distribution; Reliability; Monte Carlo simulation; Multi-state systems; multi-state components; reliability; s-dependence; universal generating function;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Reliability and Maintainability Symposium (RAMS), 2015 Annual
  • Conference_Location
    Palm Harbor, FL
  • Print_ISBN
    978-1-4799-6702-5
  • Type

    conf

  • DOI
    10.1109/RAMS.2015.7105177
  • Filename
    7105177