全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

Effect of Sample Size on the Control Limits of Exponentially Weighted Moving Average Distance Square Scheme

DOI: 10.4236/oalib.1102663, PP. 1-7

Subject Areas: Mathematical Statistics

Keywords: Average Run Length, Control Limit, Exponential Weighted Moving Average, Joint Monitoring

Full-Text   Cite this paper   Add to My Lib

Abstract

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.

References

[1]  Roberts, S.W. (1959) Control Chart Tests Based on Geometric Moving Averages. Technometrics, 1, 239-250.
http://dx.doi.org/10.1080/00401706.1959.10489860
[2]  Shewhart, W. A. (1939) Statistical Methods from the Viewpoint of Quality Control. Graduate School, Department of Agriculture, Washington DC, 75.
[3]  Crowder, S.V. (1989) Design of Exponentially Weighted Moving Average Schemes. Journal of Quality Technology, 21, 155-162.
[4]  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
[5]  Gan, F.F. (1997) Joint Monitoring of Process Mean and Variance. Nonlinear Analysis, Theory, Methods and Applications, 30, 4017-4024.
http://dx.doi.org/10.1016/S0362-546X(97)00224-1
[6]  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
[7]  Chen, G., Cheng, S.W. and Xie, H.W. (2001) Monitoring Process Mean and Variability with One EWMA Chart. Journal of Quality Technology, 33, 223-233.
[8]  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
[9]  Razmy, A.M. (2005) Joint Monitoring of Process Mean and Variance. MSc Thesis, Department of Statistics and Applied Probability, National University of Singapore, Singapore.
[10]  Quesenberry, C.P. (1995) On Properties of Q Charts Variables. Journal of Quality Technology, 21, 242-250.

Full-Text


comments powered by Disqus

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133

WeChat 1538708413