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On the bootstrap confidence intervals of the process incapability index Cpp

Author

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  • Chou, Chao-Yu
  • Lin, Yu-Chang
  • Chang, Chun-Lang
  • Chen, Chung-Ho

Abstract

The process incapability index Cpp is an indicator, introduced by Greenwich and Jahr-Schaffrath, for evaluating the capability of a process. When Cpp is applied to evaluate a process, estimating the confidence interval of Cpp is important for statistical inference on the process. Calculating the confidence interval for a process index usually needs the assumption about the underlying distribution. Bootstrapping is a non-parametric, but computer intensive, estimation method. In the present paper we report the results of a simulation study on the behavior of four 95% bootstrap confidence intervals (i.e. standard bootstrap, percentile bootstrap, biased-corrected percentile bootstrap, and biased-corrected and accelerated bootstrap) for estimating Cpp when data are from a specific Burr distribution, which is used to represent various probability distributions. A detailed discussion of the simulation results is presented and some conclusions are provided.

Suggested Citation

  • Chou, Chao-Yu & Lin, Yu-Chang & Chang, Chun-Lang & Chen, Chung-Ho, 2006. "On the bootstrap confidence intervals of the process incapability index Cpp," Reliability Engineering and System Safety, Elsevier, vol. 91(4), pages 452-459.
    • Handle: RePEc:eee:reensy:v:91:y:2006:i:4:p:452-459
    DOI: 10.1016/j.ress.2005.03.004
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    Cited by:

    1. Laggoune, Radouane & Chateauneuf, Alaa & Aissani, Djamil, 2010. "Impact of few failure data on the opportunistic replacement policy for multi-component systems," Reliability Engineering and System Safety, Elsevier, vol. 95(2), pages 108-119.
    2. Zhuang, Liangliang & Xu, Ancha & Pang, Jihong, 2021. "Product reliability analysis based on heavily censored interval data with batch effects," Reliability Engineering and System Safety, Elsevier, vol. 212(C).
    3. Zio, E. & Pedroni, N., 2009. "Building confidence in the reliability assessment of thermal-hydraulic passive systems," Reliability Engineering and System Safety, Elsevier, vol. 94(2), pages 268-281.
    4. Wang, Guodong & He, Zhen & Xue, Li & Cui, Qingan & Lv, Shanshan & Zhou, Panpan, 2017. "Bootstrap analysis of designed experiments for reliability improvement with a non-constant scale parameter," Reliability Engineering and System Safety, Elsevier, vol. 160(C), pages 114-121.

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