In the series of quality monitoring schemes with exponentially weighted
moving average, the exponentially weighted moving average distance square
scheme was introduced for joint monitoring of process mean and variance. This
scheme claims that it has a special feature that the control limits of the
scheme are independent of sample size and therefore it gives more freedom to
the users. However, this claim was not studied in detail. In this study, the
control limits were found for this scheme through simulations, for different
sample sizes with different combination of other scheme parameters. This study
concludes that the control limits for designing this scheme are independent of
sample size.
Cite this paper
Razmy, A. M. (2016). Effect of Sample Size on the Control Limits of Exponentially Weighted Moving Average Distance Square Scheme. Open Access Library Journal, 3, e2663. doi: http://dx.doi.org/10.4236/oalib.1102663.
Chang, T.C. and Gan, F.F. (1993) Optimal
Designs of One-Sided EWMA Charts for Monitoring a Process Variance. Journal of Statistical Computing & Simulations, 49, 33-48. http://dx.doi.org/10.1080/00949659408811559
Gan, F.F. (1995) Joint Monitoring of Process
Mean and Variance Using Exponentially Weighted Moving Average
Control Charts. Technometrics, 37,
446-453. http://dx.doi.org/10.1080/00401706.1995.10484377
Chen, G., Cheng, S.W. and Xie, H.W. (2004) A New EWMA Control
Chart for Monitoring Both Location and Dispersion. Quality Technology &Quantitative
Management, 1, 217-231. http://dx.doi.org/10.1080/16843703.2004.11673074
Razmy, A.M. (2005) Joint Monitoring of Process Mean and Variance.
MSc Thesis, Department of Statistics and Applied Probability, National
University of Singapore, Singapore.