IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v55y2011i5p2003-2010.html
   My bibliography  Save this article

Adaptive R charts with variable parameters

Author

Listed:
  • Lee, Pei-Hsi

Abstract

The Shewhart R control chart (R chart) has been widely used to monitor process variance. However, the main disadvantage of an R chart is its slowness to signal small increases on the variability. In this paper, ideas of adaptive control charts are extended to the Shewhart R chart for improving efficiency in signaling increases on the variance. A Markov chain model is applied to evaluate its performance. The statistical performance shows that the R chart with variable parameters (VP) is more sensitive to variance increases.

Suggested Citation

  • Lee, Pei-Hsi, 2011. "Adaptive R charts with variable parameters," Computational Statistics & Data Analysis, Elsevier, vol. 55(5), pages 2003-2010, May.
    • Handle: RePEc:eee:csdana:v:55:y:2011:i:5:p:2003-2010
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-9473(10)00454-8
    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. De Magalhaes, Maysa S. & Epprecht, Eugenio K. & Costa, Antonio F. B., 2001. "Economic design of a Vp chart," International Journal of Production Economics, Elsevier, vol. 74(1-3), pages 191-200, December.
    2. Shu, Lianjie & Jiang, Wei & Wu, Zhang, 2008. "Adaptive CUSUM procedures with Markovian mean estimation," Computational Statistics & Data Analysis, Elsevier, vol. 52(9), pages 4395-4409, May.
    3. 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.
    4. 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.
    5. 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.
    6. Luo, Yunzhao & Li, Zhonghua & Wang, Zhaojun, 2009. "Adaptive CUSUM control chart with variable sampling intervals," Computational Statistics & Data Analysis, Elsevier, vol. 53(7), pages 2693-2701, May.
    7. Giovanni Celano, 2009. "Robust design of adaptive control charts for manual manufacturing/inspection workstations," Journal of Applied Statistics, Taylor & Francis Journals, vol. 36(2), pages 181-203.
    8. Chen, Yan-Kwang & Hsieh, Kun-Lin, 2007. "Hotelling's T2 charts with variable sample size and control limit," European Journal of Operational Research, Elsevier, vol. 182(3), pages 1251-1262, November.
    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. 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.
    2. Hedegaard, Esben & Hodrick, Robert J., 2016. "Estimating the risk-return trade-off with overlapping data inference," Journal of Banking & Finance, Elsevier, vol. 67(C), pages 135-145.
    3. 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.

    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. Pei-Hsi Lee & Yi-Hsien Huang & Tsen-I Kuo & Ching-Cheng Wang, 2013. "The effect of the individual chart with variable control limits on the river pollution monitoring," Quality & Quantity: International Journal of Methodology, Springer, vol. 47(4), pages 1803-1812, June.
    2. 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.
    3. Zhang, Min & Nie, Guohua & He, Zhen, 2014. "Performance of cumulative count of conforming chart of variable sampling intervals with estimated control limits," International Journal of Production Economics, Elsevier, vol. 150(C), pages 114-124.
    4. 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.
    5. Mitra, Amitava & Lee, Kang Bok & Chakraborti, Subhabrata, 2019. "An adaptive exponentially weighted moving average-type control chart to monitor the process mean," European Journal of Operational Research, Elsevier, vol. 279(3), pages 902-911.
    6. 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.
    7. 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.
    8. Celano, Giovanni & De Magalhães, Maysa S. & Costa, Antonio F.B. & Fichera, Sergio, 2011. "A stochastic shift model for economically designed charts constrained by the process stage configuration," International Journal of Production Economics, Elsevier, vol. 132(2), pages 315-325, August.
    9. Iziy Azamsadat & Sadeghpour Gildeh Bahram & Monabbati Ehsan, 2017. "Comparison Between the Economic-Statistical Design of Double and Triple Sampling X¯\bar{X} Control Charts," Stochastics and Quality Control, De Gruyter, vol. 32(1), pages 49-61, June.
    10. 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.
    11. M. Abolmohammadi & A. Seif & M. H. Behzadi & M. B. Moghadam, 2021. "Economic statistical design of adaptive $$\bar{X}$$ X ¯ control charts based on quality loss functions," Operational Research, Springer, vol. 21(2), pages 1041-1080, June.
    12. 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.
    13. A. F. B. Costa & M. A. G. Machado, 2008. "Bivariate control charts with double sampling," Journal of Applied Statistics, Taylor & Francis Journals, vol. 35(7), pages 809-822.
    14. Su, Yan & Shu, Lianjie & Tsui, Kwok-Leung, 2011. "Adaptive EWMA procedures for monitoring processes subject to linear drifts," Computational Statistics & Data Analysis, Elsevier, vol. 55(10), pages 2819-2829, October.
    15. De Magalhaes, Maysa S. & Moura Neto, Francisco D., 2005. "Joint economic model for totally adaptive and R charts," European Journal of Operational Research, Elsevier, vol. 161(1), pages 148-161, February.
    16. Muhammad Riaz & Ronald Does, 2009. "A process variability control chart," Computational Statistics, Springer, vol. 24(2), pages 345-368, May.
    17. Lim, S.L. & Khoo, Michael B.C. & Teoh, W.L. & Xie, M., 2015. "Optimal designs of the variable sample size and sampling interval X¯ chart when process parameters are estimated," International Journal of Production Economics, Elsevier, vol. 166(C), pages 20-35.
    18. Asghar Seif & Alireza Faraz & C�dric Heuchenne & Erwin Saniga & M. B. Moghadam, 2011. "A modified economic-statistical design of the T-super-2 control chart with variable sample sizes and control limits," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(11), pages 2459-2469, January.
    19. 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.
    20. Guanfu Liu & Xiaolong Pu & Lei Wang & Dongdong Xiang, 2015. "CUSUM chart for detecting range shifts when monotonicity of likelihood ratio is invalid," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(8), pages 1635-1644, 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:55:y:2011:i:5:p:2003-2010. 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.