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Joint statistical design of X¯ and s charts with combined double sampling and variable sampling interval

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  • Lee, Pei-Hsi
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    Abstract

    A combination of double sampling and variable sampling interval (DSVSI) charts can increase the efficiency of signaling small shifts. This study proposes joint DSVSI X¯ and s charts and investigates their statistical performance. The proposed approach uses a Markov chain approach to compute the statistical performance, and uses a statistical design model to design DSVSI X¯ and s charts for detecting the mean shift and variance increase. A comparison study shows that the DSVSI X¯ and s charts are better able to signal the shifts of both mean and variance than joint double sampling X¯ and s chart, adaptive X¯ and R charts, EWMA, and CUSUM charts.

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    Bibliographic Info

    Article provided by Elsevier in its journal European Journal of Operational Research.

    Volume (Year): 225 (2013)
    Issue (Month): 2 ()
    Pages: 285-297

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    Handle: RePEc:eee:ejores:v:225:y:2013:i:2:p:285-297

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    Web page: http://www.elsevier.com/locate/eor

    Related research

    Keywords: Quality control; Double sampling chart; Variable sampling interval chart; Joint X¯ and s chart; Markov chain;

    References

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    1. Maravelakis, Petros E. & Castagliola, Philippe, 2009. "An EWMA chart for monitoring the process standard deviation when parameters are estimated," Computational Statistics & Data Analysis, Elsevier, vol. 53(7), pages 2653-2664, May.
    2. Lee, Pei-Hsi & Torng, Chau-Chen & Liao, Li-Fang, 2012. "An economic design of combined double sampling and variable sampling interval X¯ control chart," International Journal of Production Economics, Elsevier, vol. 138(1), pages 102-106.
    3. Lee, Pei-Hsi, 2011. "Adaptive R charts with variable parameters," Computational Statistics & Data Analysis, Elsevier, vol. 55(5), pages 2003-2010, May.
    4. He, David & Grigoryan, Arsen, 2006. "Joint statistical design of double sampling and s charts," European Journal of Operational Research, Elsevier, vol. 168(1), pages 122-142, January.
    5. Yu-Chang Lin & Chao-Yu Chou, 2011. "Robustness of the EWMA and the combined X� --EWMA control charts with variable sampling intervals to non-normality," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(3), pages 553-570, November.
    6. Chi-Shuan Liu & Fang-Chih Tien, 2011. "A single-featured EWMA- X control chart for detecting shifts in process mean and standard deviation," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(11), pages 2575-2596, January.
    7. Ou, Yanjing & Wu, Zhang & Goh, Thong Ngee, 2011. "A new SPRT chart for monitoring process mean and variance," International Journal of Production Economics, Elsevier, vol. 132(2), pages 303-314, August.
    8. 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.
    9. Lin, Yu-Chang & Chou, Chao-Yu, 2007. "Non-normality and the variable parameters control charts," European Journal of Operational Research, Elsevier, vol. 176(1), pages 361-373, January.
    10. Wu, Zhang & Yang, Mei & Jiang, Wei & Khoo, Michael B.C., 2008. "Optimization designs of the combined Shewhart-CUSUM control charts," Computational Statistics & Data Analysis, Elsevier, vol. 53(2), pages 496-506, December.
    11. Wu, Zhang & Yang, Mei & Khoo, Michael B.C. & Yu, Fong-Jung, 2010. "Optimization designs and performance comparison of two CUSUM schemes for monitoring process shifts in mean and variance," European Journal of Operational Research, Elsevier, vol. 205(1), pages 136-150, August.
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    Cited by:
    1. Haridy, Salah & Wu, Zhang & Lee, Ka Man & Bhuiyan, Nadia, 2013. "Optimal average sample number of the SPRT chart for monitoring fraction nonconforming," European Journal of Operational Research, Elsevier, vol. 229(2), pages 411-421.
    2. Yeong, Wai Chung & Khoo, Michael B.C. & Lee, Ming Ha & Rahim, M.A., 2013. "Economic and economic statistical designs of the synthetic X¯ chart using loss functions," European Journal of Operational Research, Elsevier, vol. 228(3), pages 571-581.

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