• DocumentCode
    2405379
  • Title

    A bayesian approach to reliability demonstration for aerospace systems

  • Author

    Yates, Scott W. ; Mosleh, Ali

  • Author_Institution
    Dept. of Mech. Eng., Maryland Univ., College Park, MD
  • fYear
    2006
  • fDate
    23-26 Jan. 2006
  • Firstpage
    611
  • Lastpage
    617
  • Abstract
    This paper presents practical methods for utilizing Bayesian techniques to improve the accuracy of reliability demonstration during acquisition of aerospace systems. The approach focuses on simple methods that can be implemented with basic knowledge of Bayesian procedures and without specialist software packages. Conjugate distributions are employed to allow rapid computation of posterior distributions for three cases: (1) probability of success in a binomial process, (2) mean time between failure with an underlying exponential distribution and (3) mean time between failure with an underlying Weibull distribution. Additionally, a method is introduced to allow partially relevant data to be introduced into the analysis with an appropriate weight applied. Possible expansions are considered for cases where more experienced analysts and better tools are available. Finally, examples of the process based on representative data are provided for both a probability of success and mean time between failure problem
  • Keywords
    Weibull distribution; aerospace engineering; belief networks; binomial distribution; failure analysis; reliability; Bayesian approach; Weibull distribution; aerospace systems; binomial process; conjugate distributions; exponential distribution; failure problem; probability; reliability demonstration; Australia; Bayesian methods; Costs; Distributed computing; Exponential distribution; Personnel; Risk analysis; Software packages; Software tools; Weibull distribution;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Reliability and Maintainability Symposium, 2006. RAMS '06. Annual
  • Conference_Location
    Newport Beach, CA
  • ISSN
    0149-144X
  • Print_ISBN
    1-4244-0007-4
  • Electronic_ISBN
    0149-144X
  • Type

    conf

  • DOI
    10.1109/RAMS.2006.1677441
  • Filename
    1677441