Comparison of Rectangular and Elliptical  Control Region EWMA Schemes for Joint  Quality Monitoring

A. M. Razmy; T. S. G. Peiris

doi:10.4236/ojs.2014.411091

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OJS> Vol.4 No.11, December 2014

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Comparison of Rectangular and Elliptical Control Region EWMA Schemes for Joint Quality Monitoring

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DOI: 10.4236/ojs.2014.411091 2,497 Downloads 2,948 Views Citations

Author(s) Leave a comment

A. M. Razmy¹, T. S. G. Peiris²

Affiliation(s)

¹Department of Mathematical Sciences, Faculty of Applied Sciences, South Eastern University of Sri Lanka, Sammanthurai, Sri Lanka.
²Department of Mathematical Sciences, Faculty of Engineering, University of Moratuwa, Moratuwa, Sri Lanka.

ABSTRACT

The exponential weighted moving average technique used in process mean and variance monitoring charts was combined by Gan in 1997 and proposed two combined joint monitoring schemes one with rectangular control region and the other with elliptical control region. Performance of these two schemes may very depend on the shifts in mean or variance to be detected quickly. In this paper, performances of these two schemes are evaluated with respect to the average run length properties. The results reveal that elliptical scheme is little faster in detecting the shifts in process mean and increase in variance within a limit.

KEYWORDS

Average Run Length, Exponential Weighted Moving Average, Joint Monitoring

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

Razmy, A. and Peiris, T. (2014) Comparison of Rectangular and Elliptical Control Region EWMA Schemes for Joint Quality Monitoring. Open Journal of Statistics, 4, 970-976. doi: 10.4236/ojs.2014.411091.

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]	Crowder, S.V. (1989) Design of Exponentially Weighted Moving Average Schemes. Journal of Quality Technology, 21, 155-162.

[3]	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

[4]	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

[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]	Crowder, S.V. (1987) A Simple Method for Studying Run Length Distribution of Exponential Weighted Moving Average Charts. Technometrics, 29, 401-407.

[7]	Lucas, J.M. and Saccuci, M.S. (1990) Exponentially Moving Average Control Schemes: Properties and Enhancements. Drexel University Faculty Working Series Paper, #87-5.