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Control charts for fraction nonconforming in a bivariate binomial process

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  • Jing-Er Chiu
  • Tsen-I Kuo

Abstract

Many multivariate quality control techniques are used for multivariate variable processes, but few work for multivariate attribute processes. To monitor multivariate attributes, controlling the false alarms (type I errors) and considering the correlation between attributes are two important issues. By taking into account these two issues, a new control chart is presented to monitor a bivariate binomial process. An example is illustrated for the proposed method. To evaluate the performance of the proposed method, a simulation study is conducted to compare the results with those using both the multivariate np chart and skewness reduction approaches. The results show that the correlation is taken into account in the designed chart and the overall false alarm is controlled at the nominal value. Moreover, the process shift can be quickly detected and the variable that is responsible for a signal can be determined.

Suggested Citation

  • Jing-Er Chiu & Tsen-I Kuo, 2010. "Control charts for fraction nonconforming in a bivariate binomial process," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(10), pages 1717-1728.
    • Handle: RePEc:taf:japsta:v:37:y:2010:i:10:p:1717-1728
    DOI: 10.1080/02664760903150698
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    References listed on IDEAS

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    1. Biswas, Atanu & Hwang, Jing-Shiang, 2002. "A new bivariate binomial distribution," Statistics & Probability Letters, Elsevier, vol. 60(2), pages 231-240, November.
    2. Bersimis, Sotiris & Psarakis, Stelios & Panaretos, John, 2006. "Multivariate Statistical Process Control Charts: An Overview," MPRA Paper 6399, University Library of Munich, Germany.
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    Cited by:

    1. Aamir Saghir & Zhengyan Lin, 2014. "Control chart for monitoring multivariate COM-Poisson attributes," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(1), pages 200-214, January.

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