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Burn-in considering yield loss and reliability gain for integrated circuits

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  • Kim, Kyungmee O.

Abstract

This paper presents burn-in effects on yield loss and reliability gain for a lifetime distribution developed from a negative binomial defect density distribution and a given defect size distribution, after assuming that the rate of defect growth is proportional to the power of the present defect size. While burn-in always results in yield loss, it creates reliability gain only if either defects grow fast or the field operation time is long. Otherwise, burn-in for a short time could result in reliability loss. The optimal burn-in time for maximizing reliability is finite if defects grow linearly in time and is infinite if defects grow nonlinearly in time. The optimal burn-in time for minimizing cost expressed in terms of both yield and reliability increases in the field operation time initially but becomes constant as the field operation time is long enough. It is numerically shown that increasing mean defect density or defect clustering increases the optimal burn-in time.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:ejores:v:212:y:2011:i:2:p:337-344
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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. 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. 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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    5. 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.
    6. Xin Liu & Thomas A. Mazzuchi, 2008. "The Optimal Burn-in: State of the Art and New Advances for Cost Function Formulation," Springer Series in Reliability Engineering, in: Hoang Pham (ed.), Recent Advances in Reliability and Quality in Design, chapter 6, pages 137-182, Springer.
    7. 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.
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    Cited by:

    1. 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.
    2. 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.
    3. 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.

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