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Optimal burn-in for maximizing reliability of repairable non-series systems

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  • Kim, Kyungmee O.
  • Kuo, Way

Abstract

Burn-in is a manufacturing process applied to products to eliminate early failures in the factory before the products reach the customers. Various methods have been proposed for determining an optimal burn-in time of a non-repairable system or a repairable series system, assuming that system burn-in improves all components in the system. In this paper, we establish the trade-off between the component reliabilities during system burn-in and develop an optimal burn-in time for repairable non-series systems to maximize reliability. One impediment to expressing the reliability of a non-series system is in that successive failures during system burn-in cannot be described precisely because a failed component is not detected until the whole system fails. For approximating the successive failures of a non-series system during system burn-in, we considered two types of repair: minimal repair at the time of system failure, and repair at the time of component or connection failure. The two types of repair provide bounds on the optimal system burn-in time of non-series systems.

Suggested Citation

  • Kim, Kyungmee O. & Kuo, Way, 2009. "Optimal burn-in for maximizing reliability of repairable non-series systems," European Journal of Operational Research, Elsevier, vol. 193(1), pages 140-151, February.
    • Handle: RePEc:eee:ejores:v:193:y:2009:i:1:p:140-151
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    References listed on IDEAS

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    1. Chang, Dong Shang, 2000. "Optimal burn-in decision for products with an unimodal failure rate function," European Journal of Operational Research, Elsevier, vol. 126(3), pages 534-540, November.
    2. 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.
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    Cited by:

    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. Zhai, Qingqing & Ye, Zhi-Sheng & Yang, Jun & Zhao, Yu, 2016. "Measurement errors in degradation-based burn-in," Reliability Engineering and System Safety, Elsevier, vol. 150(C), pages 126-135.
    6. Kim, Kyungmee O., 2011. "Burn-in considering yield loss and reliability gain for integrated circuits," European Journal of Operational Research, Elsevier, vol. 212(2), pages 337-344, July.
    7. 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.
    8. Si, Xiao-Sheng & Wang, Wenbin & Hu, Chang-Hua & Zhou, Dong-Hua, 2011. "Remaining useful life estimation - A review on the statistical data driven approaches," European Journal of Operational Research, Elsevier, vol. 213(1), pages 1-14, August.

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