IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v54y2010i10p2328-2342.html
   My bibliography  Save this article

New EWMA control charts for monitoring process dispersion

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-9473(10)00113-1
    Download Restriction: Full text for ScienceDirect subscribers only.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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.
    3. 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.
    4. Machado, Marcela A.G. & Costa, Antonio F.B., 2008. "The double sampling and the EWMA charts based on the sample variances," International Journal of Production Economics, Elsevier, vol. 114(1), pages 134-148, July.
    5. Knoth, Sven, 2006. "Computation of the ARL for CUSUM-S2 schemes," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 499-512, November.
    6. Jandhyala, Venkata K. & Fotopoulos, Stergios B. & Hawkins, Douglas M., 2002. "Detection and estimation of abrupt changes in the variability of a process," Computational Statistics & Data Analysis, Elsevier, vol. 40(1), pages 1-19, July.
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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. Ugaz Sánchez, Willy Ericson & Alonso Fernández, Andrés Modesto & Sánchez Rodríguez-Morcillo, Ismael, 2016. "Monitoring variance by EWMA charts with time varying smoothing parameter," DES - Working Papers. Statistics and Econometrics. WS 23413, Universidad Carlos III de Madrid. Departamento de Estadística.
    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Huang, Wenpo & Shu, Lianjie & Jiang, Wei, 2012. "Evaluation of exponentially weighted moving variance control chart subject to linear drifts," Computational Statistics & Data Analysis, Elsevier, vol. 56(12), pages 4278-4289.
    2. Linus Schiöler & Marianne Fris�n, 2012. "Multivariate outbreak detection," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(2), pages 223-242, April.
    3. Fan Yi & Peihua Qiu, 2023. "Water Resource Surveillance for the Salton Sea in California By Adaptive Sequential Monitoring of Its Landsat Images," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 28(3), pages 549-563, September.
    4. H. You & Michael Khoo & P. Castagliola & Yanjing Ou, 2015. "Side sensitive group runs $$\bar{{X}}$$ X ¯ chart with estimated process parameters," Computational Statistics, Springer, vol. 30(4), pages 1245-1278, December.
    5. A. F.B. Costa & M. A.G. Machado, 2011. "A control chart based on sample ranges for monitoring the covariance matrix of the multivariate processes," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(2), pages 233-245, September.
    6. Peruchi, Rogério Santana & Balestrassi, Pedro Paulo & de Paiva, Anderson Paulo & Ferreira, João Roberto & de Santana Carmelossi, Michele, 2013. "A new multivariate gage R&R method for correlated characteristics," International Journal of Production Economics, Elsevier, vol. 144(1), pages 301-315.
    7. Verdier, Ghislain & Hilgert, Nadine & Vila, Jean-Pierre, 2008. "Adaptive threshold computation for CUSUM-type procedures in change detection and isolation problems," Computational Statistics & Data Analysis, Elsevier, vol. 52(9), pages 4161-4174, May.
    8. Bersimis, Sotiris & Koutras, Markos V. & Maravelakis, Petros E., 2014. "A compound control chart for monitoring and controlling high quality processes," European Journal of Operational Research, Elsevier, vol. 233(3), pages 595-603.
    9. Lee, Pei-Hsi, 2013. "Joint statistical design of X¯ and s charts with combined double sampling and variable sampling interval," European Journal of Operational Research, Elsevier, vol. 225(2), pages 285-297.
    10. Axel Gandy & Jan Terje Kvaløy, 2013. "Guaranteed Conditional Performance of Control Charts via Bootstrap Methods," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 40(4), pages 647-668, December.
    11. 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.
    12. Max Wornowizki & Roland Fried & Simos G. Meintanis, 2017. "Fourier methods for analyzing piecewise constant volatilities," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 101(3), pages 289-308, July.
    13. Mu’azu Ramat Abujiya & Muhammad Riaz & Muhammad Hisyam Lee, 2015. "Enhanced Cumulative Sum Charts for Monitoring Process Dispersion," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-22, April.
    14. Wu, Zhang & Khoo, Michael B.C. & Shu, Lianjie & Jiang, Wei, 2009. "An np control chart for monitoring the mean of a variable based on an attribute inspection," International Journal of Production Economics, Elsevier, vol. 121(1), pages 141-147, September.
    15. Wu, Zhang & Jiao, Jianxin & He, Zhen, 2009. "A single control chart for monitoring the frequency and magnitude of an event," International Journal of Production Economics, Elsevier, vol. 119(1), pages 24-33, May.
    16. 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.
    17. 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.
    18. 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.
    19. Longcheen Huwang & Yi‐Hua Tina Wang & Arthur B. Yeh & Ze‐Shiang Jason Chen, 2009. "On the exponentially weighted moving variance," Naval Research Logistics (NRL), John Wiley & Sons, vol. 56(7), pages 659-668, October.
    20. Marianne Frisén, 2014. "Spatial outbreak detection based on inference principles for multivariate surveillance," IISE Transactions, Taylor & Francis Journals, vol. 46(8), pages 759-769, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:csdana:v:54:y:2010:i:10:p:2328-2342. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/csda .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.