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New EWMA control charts for monitoring process dispersion

Author

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  • Huwang, Longcheen
  • Huang, Chun-Jung
  • Wang, Yi-Hua Tina

Abstract

There exist two EWMA-type dispersion charts for monitoring dispersion increases in the literature. One resets the EWMA statistic to zero whenever it is below zero. The other one truncates negative normalized observations to zero in the EWMA statistic. This paper proposes two one-sided EWMA charts for detecting dispersion increases and decreases, respectively, and one two-sided EWMA chart for monitoring dispersion increases or decreases simultaneously. Simulation studies show that the proposed upper-sided EWMA chart performs better than the two existing counterparts for detecting increases in dispersion, and that the proposed lower-sided EWMA chart significantly outperforms the two lower-sided EWMA charts developed similar to their two existing upper-sided EWMA charts for detecting decreases in dispersion. Moreover, the proposed two-sided EWMA chart provides much better sensitivity than the two two-sided EWMA charts generalized from the two existing upper-sided EWMA charts for detecting overall changes in dispersion.

Suggested Citation

  • Huwang, Longcheen & Huang, Chun-Jung & Wang, Yi-Hua Tina, 2010. "New EWMA control charts for monitoring process dispersion," Computational Statistics & Data Analysis, Elsevier, vol. 54(10), pages 2328-2342, October.
    • Handle: RePEc:eee:csdana:v:54:y:2010:i:10:p:2328-2342
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    References listed on IDEAS

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    1. Ross Sparks, 2003. "Monitoring for Increases in Process Variance," Australian & New Zealand Journal of Statistics, Australian Statistical Publishing Association Inc., vol. 45(4), pages 383-394, December.
    2. Zhou, Qin & Luo, Yunzhao & Wang, Zhaojun, 2010. "A control chart based on likelihood ratio test for detecting patterned mean and variance shifts," Computational Statistics & Data Analysis, Elsevier, vol. 54(6), pages 1634-1645, June.
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    7. Human, S.W. & Chakraborti, S. & Smit, C.F., 2010. "Shewhart-type control charts for variation in phase I data analysis," Computational Statistics & Data Analysis, Elsevier, vol. 54(4), pages 863-874, April.
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    Cited by:

    1. Luiz M A Lima-Filho & Tarciana Liberal Pereira & Tatiene C Souza & Fábio M Bayer, 2020. "Process monitoring using inflated beta regression control chart," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-20, July.
    2. Guoyi Zhang, 2014. "Improved R and s control charts for monitoring the process variance," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(6), pages 1260-1273, June.
    3. Jen-Hsiang Chen & Shin-Li Lu, 2022. "Economic-Statistical Performance of Auxiliary Information-Based Maximum EWMA Charts for Monitoring Manufacturing Processes," Mathematics, MDPI, vol. 10(13), pages 1-15, July.
    4. Sofia Paulino & Manuel Cabral Morais & Sven Knoth, 2019. "On ARL-unbiased c-charts for INAR(1) Poisson counts," Statistical Papers, Springer, vol. 60(4), pages 1021-1038, August.
    5. Morais Manuel Cabral, 2016. "An ARL-Unbiased np-Chart," Stochastics and Quality Control, De Gruyter, vol. 31(1), pages 11-21, June.
    6. Muhammad Riaz & Saddam Akber Abbasi & Muhammad Abid & Abdulhammed K. Hamzat, 2020. "A New HWMA Dispersion Control Chart with an Application to Wind Farm Data," Mathematics, MDPI, vol. 8(12), pages 1-14, December.
    7. repec:cte:wsrepe:23413 is not listed on IDEAS
    8. Graham, M.A. & Chakraborti, S. & Human, S.W., 2011. "A nonparametric exponentially weighted moving average signed-rank chart for monitoring location," Computational Statistics & Data Analysis, Elsevier, vol. 55(8), pages 2490-2503, August.
    9. Graham, M.A. & Mukherjee, A. & Chakraborti, S., 2012. "Distribution-free exponentially weighted moving average control charts for monitoring unknown location," Computational Statistics & Data Analysis, Elsevier, vol. 56(8), pages 2539-2561.

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