Communications for Statistical Applications and Methods

The Korean Statistical Society (한국통계학회)
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Burn-in Models: Recent Issues, Developments and Future Topics

  • Cha, Ji-Hwan (Department of Statistics, Ewha Womans University)
  • Published : 2009.09.30
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Abstract

Recently, there has been much development on burn-in models in reliability area. Especially, the previous burn-in models have been extended to more general cases. For example, (i) burn-in procedures for repairable systems have been developed (ii) an extended assumption on the failure rate of the system has been proposed and (iii) a stochastic model for burn-in procedure in accelerated environment has been developed. In this paper, recent extensions and advances in burn-in models are introduced and some issues to be considered in the future study are discussed.

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References

  1. Beichelt, F. and Fischer, K. (1980). General failure model applied to preventive maintenance policies, IEEE Transactions on Reliability, R-29, 39-41 https://doi.org/10.1109/TR.1980.5220704
  2. Block, H. W., Li, Y. and Savits, T. H. (2003a). Initial and final behavior of failure rate functions for mixtures and systems, Journal of Applied Probability, 40, 721-740 https://doi.org/10.1239/jap/1059060898
  3. Block, H. W., Li, Y. and Savits, T. H. (2003b). Preservation of properties under mixture, Probability in the Engineering and Informational Sciences, 17, 205-212 https://doi.org/10.1017/S026996480317204X
  4. Block, H. W., Mi, J. and Savits, T. H. (1994). Some results on burn-in, Statistica Sinica, 4, 525-533
  5. Block, H. W. and Savits, T. H. (1997). Burn-in, Statistical Science, 12, 1-19 https://doi.org/10.1214/ss/1029963258
  6. Block, H. W., Savits, T. H. and Singh, H. (2002). A criterion for burn-in that balances mean residual life and residual variance, Operations Research, 50, 290-296 https://doi.org/10.1287/opre.50.2.290.435
  7. Cha, J. H. (2000). On a better burn-in procedure, Journal of Applied Probability, 37, 1099-1103 https://doi.org/10.1239/jap/1014843087
  8. Cha, J. H. (2001). Burn-in procedures for a generalized model, Journal of Applied Probability, 38, 542-553 https://doi.org/10.1239/jap/996986761
  9. Cha, J. H. (2003). A further extension of the generalized burn-in model, Journal of Applied Probability, 40, 264-270 https://doi.org/10.1239/jap/1044476840
  10. Cha, J. H. (2006a). An extended model for optimal burn-in procedures, IEEE Transactions on Relia-bility, 55, 189-198 https://doi.org/10.1109/TR.2006.874921
  11. Cha, J. H. (2006b). A stochastic model for burn-in procedures in accelerated environment, Naval Research Logistics, 53, 226-234 https://doi.org/10.1002/nav.20135
  12. Cha, J. H. and Mi, J. (2005). Optimal burn-in procedures in a generalized environment, International Journal of Reliability, Quality and Safety Engineering, 12, 189-202 https://doi.org/10.1142/S021853930500177X
  13. Cha, J. H. and Mi, J. (2008). On optimal operating conditions for a data processing system: A stochastic approach, Applied Stochastic Models in Business and Industry, 24, 31-49 https://doi.org/10.1002/asmb.v24:1
  14. Cha, J. H. and Na, M. H. (2009). Accelerated burn-in procedures and system maintenance policies, Communications in Statistics - Theory and Methods, 38, 719-733 https://doi.org/10.1080/03610920802287321
  15. Clarotti, C. A. and Spizzichino, F. (1991). Bayes burn-in decision procedures, Probability in the Engineering and Informational Sciences, 4, 437-445 https://doi.org/10.1017/S0269964800001741
  16. Finkelstein, M. and Esaulova, V. (2006). Failure rates in heterogeneous populations, In Handbook of Engineering Statistics (Ed. Pham), Springer, 369-386
  17. Jensen, F. and Petersen, N. E. (1982). Burn-in, John Wiley, New York
  18. Kececioglu, D. and Sun, F. (1995). Environmental Stress Screening: Its Qualification, Optimization, and Management, Prentice Hall, New York
  19. Klutke, G., Kiessler, P. C. and Wortman, M. A. (2003). A critical look at the bathtub curve, IEEE Transactions on Reliability, 52, 125-129 https://doi.org/10.1109/TR.2002.804492
  20. Kuo, W. and Kuo, Y. (1983). Facing the headaches of early failures: A state-of-the-art review of burn-in decisions, In Proceeding on the IEEE, 71, 1257-1266 https://doi.org/10.1109/PROC.1983.12763
  21. Meeker, W. Q. and Escobar, L. A. (1993). A review of recent research and current issues in accelerated testing, International Statistical Review, 61, 147-168 https://doi.org/10.2307/1403600
  22. Mi, J. (1991). Optimal Burn-in, Doctoral Thesis, Department Statistics, University Pittsburgh, Pittsburgh
  23. Mi, J. (1994a). Burn-in and maintenance policies, Advances in Applied Probability, 26, 207-221 https://doi.org/10.2307/1427587
  24. Mi, J. (1994b). Maximization of a survival probability and its application, Journal of Applied Proba-bility, 31, 1026-1033 https://doi.org/10.2307/3215326
  25. Mi, J. (1996). Minimizing some cost functions related to both burn-in and field use, Operations Research, 44, 497-500 https://doi.org/10.1287/opre.44.3.497
  26. Mi, J. (1997). Warranty policies and burn-in, Naval Research Logistics, 44, 199-209 https://doi.org/10.1002/(SICI)1520-6750(199703)44:2<199::AID-NAV4>3.0.CO;2-4
  27. Mi, J. (2003). Optimal burn-in time and eventually IFR, Journal of the Chinese Institute of Industrial Engineers, 20, 533-542 https://doi.org/10.1080/10170660309509258
  28. Nelson, W. (1990). Accelerated Testing: Statistical Models, Test Plans, and Data Analysis, John Wiley & Sons, New York
  29. Nguyen, D. G. and Murthy, D. N. P. (1982). Optimal burn-in time to minimize cost for products sold under warranty, lIE Transactions, 14, 167-174 https://doi.org/10.1080/05695558208975056
  30. Park, K. S. (1985). Effect of burn-in on mean residual life, IEEE Transactions on Reliability, 34, 522-523 https://doi.org/10.1109/TR.1985.5222253
  31. Ross, S. (1996). Stochastic Processes, Wiley, New York
  32. Tseng, S. T., Tang, J. and Ku, I. H. (2003). Determination of burn-in parameters and residual life for highly reliable products, Naval Research Logistics, 50, 1-14 https://doi.org/10.1002/nav.10042
  33. Weiss, G. H. and Dishon, M. (1971). Some economic problems related to burn-in programs, IEEE Transactions on Reliability, 20, 190-195 https://doi.org/10.1109/TR.1971.5216125

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