Reliability Analysis as a Tool for Expressing and Communicating Uncertainty

  • Terje Aven
Part of the Statistics for Industry and Technology book series (SIT)


A reliability analysis is supposed to be a tool for dealing with uncerainties. The analysis does not create uncertainty, but gives knowledge about the uncertainties related to the number of failures of a system, the downtime, etc. And probability is used as a measure of uncertainty. In this chapter we present main principles for execution and use of reliability analyses given this basis for the analyses. Examples are presented to illustrate the principles, in relation to the performance of a system having components being repaired or replaced at failures, and to a structural reliability analysis. The approach is compared with the classical framework for expressing and interpreting reliability, in which reliability is assumed to be a property of the system considered and the purpose of reliability analysis is to estimate this underlying true reliability.

Keywords and phrases

Foundational issues uncertainty Bayesian analysis subjective probability 


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  1. 1.
    Apostolakis, G.E. (1990). The concept of probability in safety assessments of technological systems. Science. 250, 1359–1364, 1990.CrossRefGoogle Scholar
  2. 2.
    Apostolakis, G.E. et. al. (eds.) (1988). Reliability Engineering and System Safety, special issue on The Interpretation of Probability in Probabilistic Safety Assessments, 23.Google Scholar
  3. 3.
    Aven, T. and Pörn, K. (1998). Expressing and interpreting the results of quantitative risk analyses. Reliability Engineering and System Safety. Special Issue on Offshore Safety, 61, 3–10.CrossRefGoogle Scholar
  4. 4.
    Aven, T. and Rettedal, W. (1998). Bayesian frameworks for integrating QRA and SRA. Structural Safety, 20, 155–165.CrossRefGoogle Scholar
  5. 5.
    Aven, T. and Jensen, U. (1999). Stochastic Models in Reliability, Springer Verlag, New York.zbMATHCrossRefGoogle Scholar
  6. 6.
    Aven, T. (1999). Risk analysis. Foundational issues. Paper presented at the First International Symposium on Industrial Statistics. Linkoping, 19–21 August 1999, Sweden.Google Scholar
  7. 7.
    Barlow, R. E. (1998) Engineering Reliability. SIAM, Philadelphia, Pennsylvania.zbMATHCrossRefGoogle Scholar
  8. 8.
    Barlow, R.E., Clarotti, C. and Spizzichino, F. (eds.) (1993). Reliability and Decision Making, Chapman & Hall, New York.Google Scholar
  9. 9.
    Bernando, J. and Smith, A. (1994) Bayesian Theory. Wiley, New York.CrossRefGoogle Scholar
  10. 10.
    Geisser, S. (1993) Predictive Inference: An Introduction, Chapman & Hall, New York.zbMATHGoogle Scholar
  11. 11.
    Helton, J.C. and Burmaster, D.E., (eds.) (1996). Reliability Engineering and System Safety. Special issue on Treatment of aleatory and epistemic uncertainty. 54.Google Scholar
  12. 12.
    Lindley (1985) Making Decisions, Wiley, New York.Google Scholar
  13. 13.
    NORSOK (1999). Regularity management & reliability technology, Z016. Norwegian Technology Standards Institution, Oslo.Google Scholar
  14. 14.
    Singpurwalla, N.D. (1988). Foundational issues in reliability and risk analysis. SIAM Review, 30, 264–282.MathSciNetzbMATHCrossRefGoogle Scholar
  15. 15.
    Watson, S. R. and Buede, D. M. (1987) Decision Synthesis, Cambridge University Press, New York.Google Scholar
  16. 16.
    Watson, S.R. (1994). The meaning of probability in probabilistic safety analysis. Reliability Engineering and System Safety. 45, 261–269.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2000

Authors and Affiliations

  • Terje Aven
    • 1
  1. 1.Stavanger University CollegeStavangerNorway

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