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International Journal of Quality, Statistics, and Reliability
Volume 2011 (2011), Article ID 681210, 8 pages
http://dx.doi.org/10.1155/2011/681210
Research Article

Bayesian Prediction of the Overhaul Effect on a Repairable System with Bounded Failure Intensity

Department of Operational Research, University of Delhi, Delhi 7, India

Received 13 December 2010; Revised 20 June 2011; Accepted 21 June 2011

Academic Editor: Ratna Babu Chinnam

Copyright © 2011 Preeti Wanti Srivastava and Nidhi Jain. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. H. Pham and H. Wang, “Imperfect maintenance,” European Journal of Operational Research, vol. 94, no. 3, pp. 425–438, 1996. View at Scopus
  2. M. A. K. Malik, “Reliable preventive maintenance scheduling,” AIIE Transactions, vol. 11, no. 3, pp. 221–228, 1979. View at Scopus
  3. I. Shin, T. J. Lim, and C. H. Lie, “Estimating parameters of intensity function and maintenance effect for repairable unit,” Reliability Engineering and System Safety, vol. 54, no. 1, pp. 1–10, 1996. View at Publisher · View at Google Scholar · View at Scopus
  4. L. J. Bain and M. Engelhardt, “Inferences on the parameters and current system reliability for a time truncated weibull process,” Technometrics, vol. 22, no. 3, pp. 421–426, 1980. View at Scopus
  5. L. J. Bain and M. Engelhardt, “Prediction intervals for the Weibull Process,” Technometrics, vol. 20, pp. 167–169, 1978.
  6. L. H. Crow, “Reliability analysis for complex, repairable systems,” Reliability and Biometry, vol. 13, no. 6, pp. 379–410, 1974.
  7. M. Guida, R. Calabria, and G. Pulcini, “Bayes inference for a non-homogeneous Poisson process with power intensity law,” IEEE Transactions on Reliability, vol. 38, no. 5, pp. 603–609, 1989. View at Publisher · View at Google Scholar · View at Scopus
  8. L. Lee and S. K. Lee, “Some results on inference for the weibull process,” Technometrics, vol. 20, no. 1, pp. 41–45, 1978.
  9. S. E. Rigdon and A. P. Basu, Statistical Methods for the Reliability of Repairable Systems, John Wiley, New York, NY, USA, 2000.
  10. A. Sen, “Bayesian estimation and prediction of the intensity of the power law process,” Journal of Statistical Computation and Simulation, vol. 72, no. 8, pp. 613–631, 2002. View at Publisher · View at Google Scholar · View at Scopus
  11. J. W. Yu, G. L. Tian, and M. L. Tang, “Predictive analyses for nonhomogeneous Poisson processes with power law using Bayesian approach,” Computational Statistics and Data Analysis, vol. 51, no. 9, pp. 4254–4268, 2007. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  12. D. R. Cox and P. A. W. Lewis, The Statistical Analysis of Series of Events, 1966.
  13. N. Jack, “Analysing event data from a repairable machine subject to imperfect preventive maintenance,” Quality and Reliability Engineering International, vol. 13, no. 4, pp. 183–186, 1997. View at Scopus
  14. G. Pulcini, “On the overhaul effect for repairable mechanical units: a Bayes approach,” Reliability Engineering and System Safety, vol. 70, no. 1, pp. 85–94, 2000. View at Scopus
  15. G. Pulcini, “On the prediction of future failures for a repairable equipment subject to overhauls,” Communications in Statistics, vol. 30, no. 4, pp. 691–706, 2001. View at Scopus
  16. M. Engelhardt and L. J. Bain, “On the mean time between failures for repairable systems,” IEEE Transactions on Reliability, vol. 35, no. 4, pp. 419–422, 1986. View at Scopus
  17. G. Pulcini, “A bounded intensity process for the reliability of repairable equipment,” Journal of Quality Technology, vol. 33, no. 4, pp. 480–492, 2001. View at Scopus
  18. L. Attardi and G. Pulcini, “A new model for repairable systems with bounded failure intensity,” IEEE Transactions on Reliability, vol. 54, no. 4, pp. 572–582, 2005. View at Publisher · View at Google Scholar · View at Scopus