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Minimizing Some Cost Functions Related to Both Burn-In and Field Use

Author

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  • Jie Mi

    (Florida International University, Miami, Florida)

Abstract

Burn-in procedure is used to improve the quality of products. In field operation only those components which survive the burn-in process will be used. Various additive cost functions are considered in this paper. One part of the cost function is the expense incurred until the first component surviving burn-in is obtained. The other part of cost function is either (i) the gain proportional to the mean life in field operation or (ii) the expenditure due to replacement at failure during field operation. We assume that the component before undergoing the burn-in procedure has a bathtub-shaped failure rate function with change points t 1 and t 2 . It is shown that the optimal burn-in time b * minimizing the cost function is always before t 1 . It is also shown that a large initial failure rate justifies burn-in, i.e., b * > 0.

Suggested Citation

  • Jie Mi, 1996. "Minimizing Some Cost Functions Related to Both Burn-In and Field Use," Operations Research, INFORMS, vol. 44(3), pages 497-500, June.
    • Handle: RePEc:inm:oropre:v:44:y:1996:i:3:p:497-500
    DOI: 10.1287/opre.44.3.497
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    Citations

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    Cited by:

    1. Ji Cha & Maxim S. Finkelstein, 2009. "Stochastically ordered subpopulations and optimal burn-in procedure," MPIDR Working Papers WP-2009-030, Max Planck Institute for Demographic Research, Rostock, Germany.
    2. Cha, Ji Hwan & Finkelstein, Maxim, 2010. "Burn-in by environmental shocks for two ordered subpopulations," European Journal of Operational Research, Elsevier, vol. 206(1), pages 111-117, October.
    3. Henry W. Block & Thomas H. Savits & Harshinder Singh, 2002. "A Criterion for Burn-in that Balances Mean Residual Life and Residual Variance," Operations Research, INFORMS, vol. 50(2), pages 290-296, April.
    4. Ji Hwan Cha, 2006. "A stochastic model for burn‐in procedures in accelerated environment," Naval Research Logistics (NRL), John Wiley & Sons, vol. 53(3), pages 226-234, April.
    5. Zhi-Sheng Ye & Loon-Ching Tang & Min Xie, 2014. "Bi-objective burn-in modeling and optimization," Annals of Operations Research, Springer, vol. 212(1), pages 201-214, January.
    6. Cha, Ji Hwan & Pulcini, Gianpaolo, 2016. "Optimal burn-in procedure for mixed populations based on the device degradation process history," European Journal of Operational Research, Elsevier, vol. 251(3), pages 988-998.
    7. Jie Mi, 1999. "Comparisons of renewable warranties," Naval Research Logistics (NRL), John Wiley & Sons, vol. 46(1), pages 91-106, February.
    8. Cha, Ji Hwan & Finkelstein, Maxim, 2011. "Burn-in and the performance quality measures in heterogeneous populations," European Journal of Operational Research, Elsevier, vol. 210(2), pages 273-280, April.
    9. Ibrahim Elbatal & Emrah Altun & Ahmed Z. Afify & Gamze Ozel, 2019. "The Generalized Burr XII Power Series Distributions with Properties and Applications," Annals of Data Science, Springer, vol. 6(3), pages 571-597, September.
    10. J H Cha & M Finkelstein, 2012. "Burn-in via shocks for avoiding large risks," Journal of Risk and Reliability, , vol. 226(3), pages 318-326, June.
    11. Cha, Ji Hwan & Finkelstein, Maxim, 2015. "Environmental stress screening modelling, analysis and optimization," Reliability Engineering and System Safety, Elsevier, vol. 139(C), pages 149-155.
    12. Sheu, Shey-Huei & Chien, Yu-Hung, 2005. "Optimal burn-in time to minimize the cost for general repairable products sold under warranty," European Journal of Operational Research, Elsevier, vol. 163(2), pages 445-461, June.
    13. Mohammadi, Faezeh & Izadi, Muhyiddin & Lai, Chin-Diew, 2016. "On testing whether burn-in is required under the long-run average cost," Statistics & Probability Letters, Elsevier, vol. 110(C), pages 217-224.
    14. E. Salehi & M. Asadi, 2012. "Results on the past lifetime of (n − k + 1)-out-of-n structures with nonidentical components," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 75(4), pages 439-454, May.
    15. Cha, Ji Hwan & Finkelstein, Maxim, 2013. "The failure rate dynamics in heterogeneous populations," Reliability Engineering and System Safety, Elsevier, vol. 112(C), pages 120-128.
    16. Ji Hwan Cha & Sangyeol Lee & Jie Mi, 2004. "Bounding the optimal burn‐in time for a system with two types of failure," Naval Research Logistics (NRL), John Wiley & Sons, vol. 51(8), pages 1090-1101, December.

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