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Economic design of double sampling Cpm control chart for monitoring process capability

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  • Tomohiro, Ryosuke
  • Arizono, Ikuo
  • Takemoto, Yasuhiko

Abstract

In this papers, we address a double samplimg Cpm control chart. It is well known that a double sampling scheme can reduce average sampling number in comparison with a single sampling scheme in sampling inspection. However, it is complicated and difficult to design the double sampling Cpm control chart because a judgment rule of the 2nd sampling stage depends on a record of 1st sampling stage. Therefore, this paper proposes a double sampling Cpm control chart incorporating the feature that a judgment rule of 2nd sampling stage is independent of a record of 1st sampling. The design algorithm for the proposed double sampling Cpm control chart is constructed by taking the economical operation of this control chart into the consideration. That is, the economic design of the double sampling Cpm control chart is addressed. Through some numerical comparison, it has been confirmed that the proposed double sampling Cpm control chart has an advantage in the expected total operating cost over the traditional single sampling Cpm control chart.

Suggested Citation

  • 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).
  • Handle: RePEc:eee:proeco:v:221:y:2020:i:c:s0925527319302786
    DOI: 10.1016/j.ijpe.2019.08.003
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    References listed on IDEAS

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    1. Naderkhani, Farnoosh & Makis, Viliam, 2016. "Economic design of multivariate Bayesian control chart with two sampling intervals," International Journal of Production Economics, Elsevier, vol. 174(C), pages 29-42.
    2. Franco, Bruno Chaves & Celano, Giovanni & Castagliola, Philippe & Costa, Antonio Fernando Branco, 2014. "Economic design of Shewhart control charts for monitoring autocorrelated data with skip sampling strategies," International Journal of Production Economics, Elsevier, vol. 151(C), pages 121-130.
    3. Chien-Wei Wu, 2013. "Process performance evaluation based on Taguchi capability index with the consideration of measurement errors," International Journal of Systems Science, Taylor & Francis Journals, vol. 44(8), pages 1386-1399.
    4. Asma Amdouni & Philippe Castagliola & Hassen Taleb & Giovanni Celano, 2017. "A variable sampling interval Shewhart control chart for monitoring the coefficient of variation in short production runs," International Journal of Production Research, Taylor & Francis Journals, vol. 55(19), pages 5521-5536, October.
    5. Linguo Gong & Wushong Jwo & Kwei Tang, 1997. "Using On-Line Sensors in Statistical Process Control," Management Science, INFORMS, vol. 43(7), pages 1017-1028, July.
    6. Kuen-Suan Chen & Kung-Jeng Wang & Tsang-Chuan Chang, 2017. "A novel approach to deriving the lower confidence limit of indices , , and in assessing process capability," International Journal of Production Research, Taylor & Francis Journals, vol. 55(17), pages 4963-4981, September.
    7. Torng, Chau-Chen & Lee, Pei-Hsi & Liao, Nai-Yi, 2009. "An economic-statistical design of double sampling control chart," International Journal of Production Economics, Elsevier, vol. 120(2), pages 495-500, August.
    8. 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.
    9. Epprecht, Eugenio K. & Aparisi, Francisco & Ruiz, Omar & Veiga, Álvaro, 2013. "Reducing sampling costs in multivariate SPC with a double-dimension T2 control chart," International Journal of Production Economics, Elsevier, vol. 144(1), pages 90-104.
    10. Ho, Linda Lee & Aparisi, Francisco, 2016. "ATTRIVAR: Optimized control charts to monitor process mean with lower operational cost," International Journal of Production Economics, Elsevier, vol. 182(C), pages 472-483.
    11. Faraz, Alireza & Heuchenne, Cedric & Saniga, Erwin, 2017. "An Exact Method for Designing Shewhart X and S2 Control Charts to Guarantee In-Control Performance," LIDAM Discussion Papers ISBA 2017031, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    12. Lee Ho, Linda & Quinino, Roberto Costa, 2013. "An attribute control chart for monitoring the variability of a process," International Journal of Production Economics, Elsevier, vol. 145(1), pages 263-267.
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    Cited by:

    1. Li, Wanhong & Liu, Guangzhong, 2022. "Dynamic failure mode analysis approach based on an improved Taguchi process capability index," Reliability Engineering and System Safety, Elsevier, vol. 218(PB).

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