• DocumentCode
    2965461
  • Title

    Availability assessment of stochastic multi-states systems based on UGF and taking into account data uncertainty

  • Author

    El Falou, Mohamad ; Châtelet, E.

  • Author_Institution
    Inst. Charles Delaunay, Univ. de Technol. de Troyes, Troyes, France
  • fYear
    2009
  • fDate
    8-11 Dec. 2009
  • Firstpage
    1170
  • Lastpage
    1174
  • Abstract
    The presented method extends availability assessment in multi state systems to take into account data uncertainty. Until now, propagation of uncertainty is evaluated only in the classical block diagrams methods or specific simulation modeling. Using the universal generating function technique (UGF), the number of states in the multi states model is reduced and the uncertainty evaluation is generalized. Markov processes describe the multiple degradation states of components (with exponential laws) which are combined with UGF to generate the system states. The reparations are also taking into account in terms of exponential laws. The data uncertainty is modeled by usual probability functions. The results show the influence of these uncertainties on the probability states, availability assessment and consequently the decision for system design or maintenance policy. The suggested method is sufficiently general to cover many types of systems and application processes.
  • Keywords
    Markov processes; Monte Carlo methods; large-scale systems; Markov process; availability assessment; data uncertainty modeling; multistate systems; probability function; universal generating function technique; Availability; Bridges; Condition monitoring; Degradation; Markov processes; Modeling; Probability density function; Risk analysis; Stochastic systems; Uncertainty; Markov process; Monte Carlo simulation; Universal Generating Function; data uncertainty; uncertainty propagation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Engineering and Engineering Management, 2009. IEEM 2009. IEEE International Conference on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-1-4244-4869-2
  • Electronic_ISBN
    978-1-4244-4870-8
  • Type

    conf

  • DOI
    10.1109/IEEM.2009.5372978
  • Filename
    5372978