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EWMA Chart and Measurement Error

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  • Petros Maravelakis
  • John Panaretos
  • Stelios Psarakis

Abstract

Measurement error is a usually met distortion factor in real-world applications that influences the outcome of a process. In this paper, we examine the effect of measurement error on the ability of the EWMA control chart to detect out-of-control situations. The model used is the one involving linear covariates. We investigate the ability of the EWMA chart in the case of a shift in mean. The effect of taking multiple measurements on each sampled unit and the case of linearly increasing variance are also examined. We prove that, in the case of measurement error, the performance of the chart regarding the mean is significantly affected.

Suggested Citation

  • 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.
    • Handle: RePEc:taf:japsta:v:31:y:2004:i:4:p:445-455
    DOI: 10.1080/02664760410001681738
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    References listed on IDEAS

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    1. G. Robin Henderson, 2001. "EWMA and industrial applications to feedback adjustment and control," Journal of Applied Statistics, Taylor & Francis Journals, vol. 28(3-4), pages 399-407.
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    Citations

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    Cited by:

    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    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. 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.

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      More about this item

      Keywords

      Exponentially Weighted Moving Average Control Chart; Average Run Length; Average Time To Signal; Measurement Error; Markov Chain; Statistical Process Control;
      All these keywords.

      JEL classification:

      • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

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