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Production yield measure for multiple characteristics processes based on $${S_{pk}^T}$$ under multiple samples

Author

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  • W. Pearn
  • Ching-Ho Yen
  • Dong-Yuh Yang

Abstract

Process yield is an important criterion used in the manufacturing industry for measuring process performance. Methods for measuring yield for processes with single characteristic have been investigated extensively. However, methods for measuring yield for processes with multiple characteristics have been comparatively neglected. Chen et al. (Qual Reliab Eng Int 19:101–110, 2003) proposed a measurement formula called $${S_{pk}^T }$$ , which provides an exact measure of the overall process yield, for processes with multiple characteristics. In this paper, we considered the natural estimator of $${S_{pk}^T }$$ under multiple samples, and derived the asymptotic distribution for the estimator. In addition, a comparison between the SB (standard bootstrap) and the proposed method based on the lower confidence bound is executed. Generally, the result indicates that the proposed approach is more reliable than the standard bootstrap method. Copyright Springer-Verlag 2012

Suggested Citation

  • W. Pearn & Ching-Ho Yen & Dong-Yuh Yang, 2012. "Production yield measure for multiple characteristics processes based on $${S_{pk}^T}$$ under multiple samples," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 20(1), pages 65-85, March.
  • Handle: RePEc:spr:cejnor:v:20:y:2012:i:1:p:65-85
    DOI: 10.1007/s10100-010-0152-9
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