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GS2: An optimized attribute control chart to monitor process variability

Author

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  • Bezerra, Erica Leandro
  • Ho, Linda Lee
  • da Costa Quinino, Roberto

Abstract

Precise measurement of quality characteristics is expensive and time-consuming and requires instrument calibration. Furthermore, in destructive experiments, the sampled units are damaged and must be discarded. In these cases, an alternative is the classification of each sampled unit into a group using a device such as gauge rings. Operationally, this method is faster, and no measurement is taken on the sampled unit. In this paper, a new attribute control chart is proposed to monitor process variability. The statistic GS2 is calculated, and the chart signals whenever GS2>CLG, where CLG is the control limit that is determined to satisfy a desired value of ARL0 and to minimize ARL1.

Suggested Citation

  • Bezerra, Erica Leandro & Ho, Linda Lee & da Costa Quinino, Roberto, 2018. "GS2: An optimized attribute control chart to monitor process variability," International Journal of Production Economics, Elsevier, vol. 195(C), pages 287-295.
    • Handle: RePEc:eee:proeco:v:195:y:2018:i:c:p:287-295
    DOI: 10.1016/j.ijpe.2017.10.023
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    Cited by:

    1. Simões, Felipe Domingues & Costa, Antonio Fernando Branco & Machado, Marcela Aparecida Guerreiro, 2020. "The Trinomial ATTRIVAR control chart," International Journal of Production Economics, Elsevier, vol. 224(C).
    2. Tomohiro, Ryosuke & Arizono, Ikuo & Takemoto, Yasuhiko, 2020. "Economic design of double sampling Cpm control chart for monitoring process capability," International Journal of Production Economics, Elsevier, vol. 221(C).

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