IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v266y2018i1p147-167.html
   My bibliography  Save this article

Optimal design of Shewhart–Lepage type schemes and its application in monitoring service quality

Author

Listed:
  • Mukherjee, Amitava
  • Sen, Rudra

Abstract

We generalize popular distribution-free (nonparametric) Shewhart–Lepage scheme for simultaneously monitoring of location and scale parameters using an adaptive approach. This approach is known as percentile modifications of ranks (or adaptive Gastwirth score) in the statistical literature. This is a powerful tool to improve rank tests to detect a shift in the process. The adaptive Gastwirth score is not much familiar among quality control practitioners and therefore rarely used in practice. Nevertheless, such scores are very useful in detecting various types of shifts in the process characteristics. Considering its distinct advantages, we develop a new class of Shewhart-type adaptive Lepage–Gastwirth (ALG) scheme. We discuss optimal implementation strategies of the proposed scheme to achieve lower out-of-control (OOC) average run length (ARL) and false alarm rate (FAR). This scheme is typically designed to monitor service quality where the reference sample may be non-normal. Post signal follow-up procedures of the proposed Shewhart-type optimal ALG chart is discussed. We illustrate the use of optimal ALG charts with a recent data on Vancouver city call centre service quality monitoring.

Suggested Citation

  • Mukherjee, Amitava & Sen, Rudra, 2018. "Optimal design of Shewhart–Lepage type schemes and its application in monitoring service quality," European Journal of Operational Research, Elsevier, vol. 266(1), pages 147-167.
    • Handle: RePEc:eee:ejores:v:266:y:2018:i:1:p:147-167
    DOI: 10.1016/j.ejor.2017.09.013
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221717308032
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ejor.2017.09.013?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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. 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.
    2. 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.
    3. Marco Marozzi, 2014. "The multisample Cucconi test," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 23(2), pages 209-227, June.
    4. Marco Marozzi, 2009. "Some notes on the location–scale Cucconi test," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 21(5), pages 629-647.
    5. 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.
    6. 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.
    7. Amitava Mukherjee & Rudra Sen, 2015. "Comparisons of Shewhart-type rank based control charts for monitoring location parameters of univariate processes," International Journal of Production Research, Taylor & Francis Journals, vol. 53(14), pages 4414-4445, July.
    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. Song, Zhi & Mukherjee, Amitava & Liu, Yanchun & Zhang, Jiujun, 2019. "Optimizing joint location-scale monitoring – An adaptive distribution-free approach with minimal loss of information," European Journal of Operational Research, Elsevier, vol. 274(3), pages 1019-1036.
    2. Song, Zhi & Mukherjee, Amitava & Zhang, Jiujun, 2021. "Some robust approaches based on copula for monitoring bivariate processes and component-wise assessment," European Journal of Operational Research, Elsevier, vol. 289(1), pages 177-196.
    3. Rolando Rubilar-Torrealba & Karime Chahuán-Jiménez & Hanns de la Fuente-Mella, 2022. "Analysis of the Growth in the Number of Patents Granted and Its Effect over the Level of Growth of the Countries: An Econometric Estimation of the Mixed Model Approach," Sustainability, MDPI, vol. 14(4), pages 1-12, February.
    4. Eftychia Mamzeridou & Athanasios C. Rakitzis, 2023. "A Combined Runs Rules Scheme for Monitoring General Inflated Poisson Processes," Mathematics, MDPI, vol. 11(22), pages 1-16, November.
    5. Muhammad Riaz & Muhammad Abid & Hafiz Zafar Nazir & Saddam Akber Abbasi, 2019. "An enhanced nonparametric EWMA sign control chart using sequential mechanism," PLOS ONE, Public Library of Science, vol. 14(11), pages 1-15, November.
    6. Yamaguchi, Hikaru & Murakami, Hidetoshi, 2023. "The multi-aspect tests in the presence of ties," Computational Statistics & Data Analysis, Elsevier, vol. 180(C).

    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. Serguei Rouzinov & André Berchtold, 2022. "Regression-Based Approach to Test Missing Data Mechanisms," Data, MDPI, vol. 7(2), pages 1-28, January.
    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.
    3. 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.
    4. Song, Zhi & Mukherjee, Amitava & Liu, Yanchun & Zhang, Jiujun, 2019. "Optimizing joint location-scale monitoring – An adaptive distribution-free approach with minimal loss of information," European Journal of Operational Research, Elsevier, vol. 274(3), pages 1019-1036.
    5. Chenglong Li & Amitava Mukherjee & Qin Su & Min Xie, 2016. "Optimal design of a distribution-free quality control scheme for cost-efficient monitoring of unknown location," International Journal of Production Research, Taylor & Francis Journals, vol. 54(24), pages 7259-7273, December.
    6. 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.
    7. Song, Zhi & Mukherjee, Amitava & Zhang, Jiujun, 2021. "Some robust approaches based on copula for monitoring bivariate processes and component-wise assessment," European Journal of Operational Research, Elsevier, vol. 289(1), pages 177-196.
    8. 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.
    9. 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.
    10. Marco Marozzi, 2014. "The multisample Cucconi test," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 23(2), pages 209-227, June.
    11. 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.
    12. 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.
    13. Takuya Nishino & Hidetoshi Murakami, 2019. "The Cucconi statistic for Type-I censored data," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 82(8), pages 903-929, November.
    14. Dominika Polko-Zając, 2019. "On Permutation Location–Scale Tests," Statistics in Transition New Series, Polish Statistical Association, vol. 20(4), pages 153-166, December.
    15. Polko-Zając Dominika, 2019. "On Permutation Location–Scale Tests," Statistics in Transition New Series, Polish Statistical Association, vol. 20(4), pages 153-166, December.
    16. Mohammad Abdullah & Mohammad Ashraful Ferdous Chowdhury & Ajim Uddin & Syed Moudud‐Ul‐Huq, 2023. "Forecasting nonperforming loans using machine learning," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1664-1689, November.
    17. Muhammad Riaz & Ronald Does, 2009. "A process variability control chart," Computational Statistics, Springer, vol. 24(2), pages 345-368, May.
    18. Ou, Yanjing & Wu, Zhang & Tsung, Fugee, 2012. "A comparison study of effectiveness and robustness of control charts for monitoring process mean," International Journal of Production Economics, Elsevier, vol. 135(1), pages 479-490.
    19. 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.
    20. 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.

    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:ejores:v:266:y:2018:i:1:p:147-167. 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/eor .

    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.