IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v8y2020i5p706-d353575.html
   My bibliography  Save this article

On Phase-I Monitoring of Process Location Parameter with Auxiliary Information-Based Median Control Charts

Author

Listed:
  • Shahid Hussain

    (Faculty of Science, Institute of Applied Systems Analysis, Jiangsu University, Zhenjiang 212013, China
    Department of Mathematics, COMSATS University Islamabad, Attock Campus, Attock 43600, Pakistan)

  • Sun Mei

    (Faculty of Science, Institute of Applied Systems Analysis, Jiangsu University, Zhenjiang 212013, China)

  • Muhammad Riaz

    (Department of Mathematics and Statistics, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia)

  • Saddam Akber Abbasi

    (Department of Mathematics, Statistics, and Physics, Qatar University, Doha 2713, Qatar)

Abstract

A control chart is often used to monitor the industrial or services processes to improve the quality of the products. Mostly, the monitoring of location parameters, both in Phase I and Phase II, is done using a mean control chart with the assumption that the process is free from outliers or the estimators are correctly estimated from in-control samples. Generally, there are question marks about such kind of narratives. The performance of the mean chart is highly affected in the presence of outliers. Therefore, the median chart is an attractive alternative to the mean chart in this situation. The control charts are usually implemented in two phases: Phase I (retrospective) and Phase II (prospective/monitoring). The efficiency of any control chart in Phase II depends on the accuracy of control limits obtained from Phase I. The current study focuses on the Phase I analysis of location parameters using median control charts. We examined the performance of different auxiliary information-based median control charts and compared the results with the usual median chart. Standardized variance and relative efficacy are used as performance measures to evaluate the efficiency of median estimators. Moreover, the probability to signal measure is used to evaluate the performance of proposed control charts to detect any potential changes in the process. The results revealed that the proposed auxiliary information based median control charts perform better in Phase I analysis. In addition, a practical illustration of an industrial scenario demonstrated the significance of the proposed control charts, in which the monitoring of concrete compressive strength is emphasized.

Suggested Citation

  • Shahid Hussain & Sun Mei & Muhammad Riaz & Saddam Akber Abbasi, 2020. "On Phase-I Monitoring of Process Location Parameter with Auxiliary Information-Based Median Control Charts," Mathematics, MDPI, vol. 8(5), pages 1-21, May.
  • Handle: RePEc:gam:jmathe:v:8:y:2020:i:5:p:706-:d:353575
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/8/5/706/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/8/5/706/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Faraz, Alireza & Woodall, William H. & Heuchenne, Cedric, 2015. "Guaranteed conditional performance of the S^2 control chart with estimated parameters," LIDAM Reprints ISBA 2015037, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    2. Muhammad Riaz, 2008. "Monitoring process mean level using auxiliary information," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 62(4), pages 458-481, November.
    3. Philippe Castagliola & Fernanda Otilia Figueiredo, 2013. "The median chart with estimated parameters," European Journal of Industrial Engineering, Inderscience Enterprises Ltd, vol. 7(5), pages 594-614.
    4. Alireza Faraz & William H. Woodall & C. Heuchenne, 2015. "Guaranteed conditional performance of the S2 control chart with estimated parameters," International Journal of Production Research, Taylor & Francis Journals, vol. 53(14), pages 4405-4413, July.
    5. Faraz, Alireza & Woodall, William & Heuchenne, Cedric, 2015. "Guaranteed conditional performance of the S^2 control chart with estimated parameters," LIDAM Discussion Papers ISBA 2015004, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    6. XueLong Hu & Philippe Castagliola & XiaoJian Zhou & AnAn Tang, 2019. "Conditional design of the EWMA median chart with estimated parameters," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 48(8), pages 1871-1889, April.
    Full references (including those not matched with items on IDEAS)

    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. Wei-Heng Huang, 2022. "The Performance of S Control Charts for the Lognormal Distribution with Estimated Parameters," Sustainability, MDPI, vol. 14(24), pages 1-16, December.
    2. Weiß, Christian H. & Steuer, Detlef & Jentsch, Carsten & Testik, Murat Caner, 2018. "Guaranteed conditional ARL performance in the presence of autocorrelation," Computational Statistics & Data Analysis, Elsevier, vol. 128(C), pages 367-379.
    3. Muhammad Aslam & Nasrullah Khan & Chi-Hyuck Jun, 2016. "A control chart using belief information for a gamma distribution," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 26(4), pages 5-19.
    4. Muhammad Riaz & Ronald Does, 2009. "A process variability control chart," Computational Statistics, Springer, vol. 24(2), pages 345-368, May.
    5. Mehwish Butt & Hafiza Farwa Amin & Javed Iqbal & Maqbool Hussain Sial & Najam-ul Hassan & Mueen-ud-Din Azad, 2023. "Homogeneously Weighted Moving Average Control Chart for Rayleigh Distribution," Bulletin of Business and Economics (BBE), Research Foundation for Humanity (RFH), vol. 12(3), pages 366-384.
    6. 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.
    7. Johannssen, Arne & Chukhrova, Nataliya & Castagliola, Philippe, 2022. "The performance of the hypergeometric np chart with estimated parameter," European Journal of Operational Research, Elsevier, vol. 296(3), pages 873-899.

    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:gam:jmathe:v:8:y:2020:i:5:p:706-:d:353575. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.