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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
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    References listed on IDEAS

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    1. 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.
    2. 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.
    3. 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.
    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.
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    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.

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