Reliability Estimation of Series-Parallel Systems Using Component Failure Data

부품의 고장자료를 이용하여 직병렬 시스템의 신뢰도를 추정하는 방법

  • Received : 2009.02.17
  • Accepted : 2009.07.27
  • Published : 2009.09.01

Abstract

In the early design stage, system reliability must be estimated from life testing data at the component level. Previously, a point estimate of system reliability was obtained from the unbiased estimate of the component reliability after assuming that the number of failed components for a given time followed a binomial distribution. For deriving the confidence interval of system reliability, either the lognormal distribution or the normal approximation of the binomial distribution was assumed for the estimator of system reliability. In this paper, a new estimator is used for the component level reliability, which is biased but has a smaller mean square error than the previous one. We propose to use the beta distribution rather than the lognormal or approximated normal distribution for developing the confidence interval of the system reliability. A numerical example based on Monte Carlo simulation illustrates advantages of the proposed approach over the previous approach.

Keywords

References

  1. Barlow, R. E. and Proschan, F. (1975), Statistical Theory of Reliability and Life Testing, Holt, Rinehart andWinston, New York
  2. Casella, G. and Berger, R. (1990), Statistical Inference, Wadworth and Brooks, California
  3. Coit, D.W. (1997), System reliability confidence intervals for complex systems with estimated component reliability, IEEE Transactions onReliability, 46(4), 487-493 https://doi.org/10.1109/24.693781
  4. Gertsbakh, I. B. (1989), Statistical ReliabilityTheory, Marcel Dekker
  5. Gertsbakh, I. B. (1982), Confidence limits for highly reliable cohereht systems with exponentially distributed lifetimes, Journal of American Statistical Association,77, 673-678 https://doi.org/10.2307/2287735
  6. Grubbs, F. E. (1971), Approximate confidence bounds for the reliability of a series systemforwhich each component has an exponential time-to-fail distribution, Technometrics, 13, 865-871 https://doi.org/10.2307/1266962
  7. Jin, T. and Coit,D.W. (2008),Unbiased variance estimates for systemreliability estimate using block decompositions, IEEE Transactions on Reliability, 57(3), 458-464 https://doi.org/10.1109/TR.2008.927809
  8. Lieberman, L. and Ross, S.M. (1971), Confidence limits for independent series system, Journal of American Statistical Association, 66, 837-840 https://doi.org/10.2307/2284237
  9. Mawaziny, A.H. andBuehler, R. J. (1967), Confidence limits for the reliability of a series system, Journal of American Statistical Association, 62, 1452-1459 https://doi.org/10.2307/2283789
  10. Rmirez-Marquez, J. E. and Jiang,W. (2006),On improved confidence bounds for system reliability, IEEE Transactions on Reliability, 55(1), 26-36 https://doi.org/10.1109/TR.2005.863814
  11. WassermanG. S. (2003),ReliabilityVerification, Testing, andAnalysis inEngineering Design, Marcel Dekker Inc