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Comparison of p control charts for low defective rate

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  • Wang, Hsiuying

Abstract

It is well known that the conventional p control chart constructed by the normal approximation for the binomial distribution suffers a serious inaccuracy in the monitor process when the true rate of nonconforming items is small. A similar problem also arises in the binomial confidence interval estimation. Adjusted confidence intervals are established in the literature to improve the coverage probability when the binomial proportion is small. In this paper, a new p control chart based on an adjusted confidence interval is established, which can substantially improve the existing control charts when the nonconforming rate is small.

Suggested Citation

  • Wang, Hsiuying, 2009. "Comparison of p control charts for low defective rate," Computational Statistics & Data Analysis, Elsevier, vol. 53(12), pages 4210-4220, October.
    • Handle: RePEc:eee:csdana:v:53:y:2009:i:12:p:4210-4220
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    References listed on IDEAS

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    1. Wang, Hsiuying, 2008. "Coverage probability of prediction intervals for discrete random variables," Computational Statistics & Data Analysis, Elsevier, vol. 53(1), pages 17-26, September.
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    Cited by:

    1. Emura, Takeshi & Lai, Ching-Chieh & Sun, Li-Hsien, 2023. "Change point estimation under a copula-based Markov chain model for binomial time series," Econometrics and Statistics, Elsevier, vol. 28(C), pages 120-137.
    2. Emura, Takeshi & Lin, Yi-Shuan, 2013. "A comparison of normal approximation rules for attribute control charts," MPRA Paper 51029, University Library of Munich, Germany.
    3. Nasrullah Khan & Muhammad Aslam & Kyung-Jun Kim & Chi-Hyuck Jun, 2017. "A mixed control chart adapted to the truncated life test based on the Weibull distribution," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 27(1), pages 43-55.
    4. Bersimis, Sotiris & Koutras, Markos V. & Maravelakis, Petros E., 2014. "A compound control chart for monitoring and controlling high quality processes," European Journal of Operational Research, Elsevier, vol. 233(3), pages 595-603.

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