IDEAS home Printed from https://ideas.repec.org/a/ids/eujine/v10y2016i2p224-242.html
   My bibliography  Save this article

Effect of measurement errors on the VSI X chart

Author

Listed:
  • XueLong Hu
  • Philippe Castagliola
  • JinSheng Sun
  • Michael Boon Chong Khoo

Abstract

Measurement errors often exist in quality control applications. In this paper, the performance of the variable sampling interval (VSI) X chart is investigated when measurement errors exist using a linearly covariate error model. It is shown that the performance of the VSI X chart is significantly affected by the presence of measurement errors. The effect of taking multiple measurements, for each item in a subgroup, on the performance of VSI X chart is also investigated in this paper. An example is provided in order to illustrate the application of the VSI X chart with measurement errors. [Received 15 October 2014; Revised 9 February 2015; Accepted 1 August 2015]

Suggested Citation

  • XueLong Hu & Philippe Castagliola & JinSheng Sun & Michael Boon Chong Khoo, 2016. "Effect of measurement errors on the VSI X chart," European Journal of Industrial Engineering, Inderscience Enterprises Ltd, vol. 10(2), pages 224-242.
    • Handle: RePEc:ids:eujine:v:10:y:2016:i:2:p:224-242
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=75853
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    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. Petros Maravelakis & John Panaretos & Stelios Psarakis, 2004. "EWMA Chart and Measurement Error," Journal of Applied Statistics, Taylor & Francis Journals, vol. 31(4), pages 445-455.
    2. Hans-Joachim Mittag & Dietmar Stemann, 1998. "Gauge imprecision effect on the performance of the X-S control chart," Journal of Applied Statistics, Taylor & Francis Journals, vol. 25(3), pages 307-317.
    3. Antonio F. B. Costa & Philippe Castagliola, 2011. "Effect of measurement error and autocorrelation on the X¯ chart," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(4), pages 661-673, December.
    4. Petros E. Maravelakis, 2012. "Measurement error effect on the CUSUM control chart," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(2), pages 323-336, May.
    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. Tilottama Chakraborty & Mrinmoy Majumder, 2019. "Application of statistical charts, multi-criteria decision making and polynomial neural networks in monitoring energy utilization of wave energy converters," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 21(1), pages 199-219, February.

    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. Chakraborty Ashit B. & Khurshid Anwer, 2013. "Measurement Error Effect on the Power of Control Chart for the Ratio of Two Poisson Distributions," Stochastics and Quality Control, De Gruyter, vol. 28(1), pages 15-21, October.
    2. K.P. Tran & P. Castagliola & G. Celano, 2016. "The performance of the Shewhart-RZ control chart in the presence of measurement error," International Journal of Production Research, Taylor & Francis Journals, vol. 54(24), pages 7504-7522, December.
    3. Petros E. Maravelakis, 2012. "Measurement error effect on the CUSUM control chart," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(2), pages 323-336, May.
    4. Su-Fen Yang & Li-Pang Chen & Cheng-Kuan Lin, 2023. "Adjustment of Measurement Error Effects on Dispersion Control Chart with Distribution-Free Quality Variable," Sustainability, MDPI, vol. 15(5), pages 1-19, February.
    5. Isabel González & Ismael Sánchez, 2009. "On‐line evaluation of the stability of an inspection process," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 25(6), pages 719-736, November.
    6. Imad Khan & Muhammad Noor-ul-Amin & Dost Muhammad Khan & Salman A. AlQahtani & Mostafa Dahshan & Umair Khalil, 2023. "Monitoring of Location Parameters with a Measurement Error under the Bayesian Approach Using Ranked-Based Sampling Designs with Applications in Industrial Engineering," Sustainability, MDPI, vol. 15(8), pages 1-18, April.
    7. Roberto Campos Leoni & Marcela Aparecida Guerreiro Machado & Antonio Fernando Branco Costa, 2016. "The T -super-2 chart with mixed samples to control bivariate autocorrelated processes," International Journal of Production Research, Taylor & Francis Journals, vol. 54(11), pages 3294-3310, June.
    8. E. Andersson & D. Bock & M. Frisen, 2006. "Some statistical aspects of methods for detection of turning points in business cycles," Journal of Applied Statistics, Taylor & Francis Journals, vol. 33(3), pages 257-278.
    9. Leoni, Roberto Campos & Costa, Antonio Fernando Branco & Machado, Marcela Aparecida Guerreiro, 2015. "The effect of the autocorrelation on the performance of the T2 chart," European Journal of Operational Research, Elsevier, vol. 247(1), pages 155-165.
    10. Suh, Jong Hwan, 2015. "Forecasting the daily outbreak of topic-level political risk from social media using hidden Markov model-based techniques," Technological Forecasting and Social Change, Elsevier, vol. 94(C), pages 115-132.
    11. Wenhui Liu & Zhonghua Li & Zhaojun Wang, 2022. "Monitoring of Linear Profiles Using Linear Mixed Model in the Presence of Measurement Errors," Mathematics, MDPI, vol. 10(24), pages 1-17, December.
    12. Antonio F. B. Costa & Philippe Castagliola, 2011. "Effect of measurement error and autocorrelation on the X¯ chart," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(4), pages 661-673, December.
    13. Muhammad Riaz & Babar Zaman & Ishaq Adeyanju Raji & M. Hafidz Omar & Rashid Mehmood & Nasir Abbas, 2022. "An Adaptive EWMA Control Chart Based on Principal Component Method to Monitor Process Mean Vector," Mathematics, MDPI, vol. 10(12), pages 1-27, June.

    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:ids:eujine:v:10:y:2016:i:2:p:224-242. 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: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=210 .

    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.