OPTIMAL BURN-IN TIME AND EVENTUALLY IFR

ABSTRACT Burn-in is a widely used technique for improving the quality of products after they have been produced. The quality of product can be measured by certain reliability characteristics such as survival probability, mean residual life, etc. In some situations, optimal burn-in need to be determined to maximize these reliability characteristics. However, burn-in is costly, and thus cost structure should be considered. Therefore, optimal burn-in time should also be determined to minimize certain cost functions. In the literature, assuming the failure rate function of the products has a bathtub shape it has been shown that the optimal burn-in time should not exceed the first change point of the failure rate function. Instead of bathtub shaped failure rate function, this paper considers the more general eventually IFR and has found that the optimal burn-in time for the objective functions studied in the literature should not exceed the first wear-out point of the eventually IFR.

[1]  B. Bergman On reliability theory and its applications , 1985 .

[2]  R. Vollertsen,et al.  Burn-In , 1999, 1999 IEEE International Integrated Reliability Workshop Final Report (Cat. No. 99TH8460).

[3]  Jie Mi,et al.  Minimizing Some Cost Functions Related to Both Burn-In and Field Use , 1996, Oper. Res..

[4]  R. L. Launer,et al.  Graphical techniques for analyzing failure data with the percentile residual-life function , 1993 .

[5]  D. N. P. Murthy,et al.  Optimal Burn-in Time to Minimize Cost for Products Sold Under Warranty , 1982 .

[6]  Harry Joe,et al.  Percentile Residual Life Functions , 1984, Oper. Res..

[7]  Way Kuo,et al.  Facing the headaches of early failures: A state-of-the-art review of burn-in decisions , 1983, Proceedings of the IEEE.

[8]  J. Cha On a better burn-in procedure , 2000, Journal of Applied Probability.

[9]  Enrico Gobbetti,et al.  Encyclopedia of Electrical and Electronics Engineering , 1999 .

[10]  Henry W. Block,et al.  BATHTUB FUNCTIONS AND BURN-IN , 1999 .

[11]  Bo Bergman,et al.  Burn–in models and ttt-transforms , 1985 .

[12]  Jie Mi Maximization of a survival probability and its application , 1994 .

[13]  J. Cha Burn-in procedures for a generalized model , 2001, Journal of Applied Probability.

[14]  Way Kuo,et al.  Facing the headaches of early failures: A state-of-the-art review of burn-in decisions , 1983 .

[15]  Kwei Tang,et al.  Burn‐in Time and Estimation of Change‐Point with Weibull‐Exponential Mixture Distribution* , 1992 .

[16]  Jie Mi,et al.  Warranty policies and burn-in , 1997 .

[17]  W. Kuo,et al.  Burn-in optimization under reliability and capacity restrictions , 1989 .

[18]  Jie Mi Bathtub failure rate and upside-down bathtub mean residual life , 1995 .

[19]  Fabio Spizzichino,et al.  Bayes Burn-In Decision Procedures , 1990 .

[20]  W. Kuo Reliability Enhancement Through Optimal Burn-In , 1984, IEEE Transactions on Reliability.