A generalized EWMA control chart and its comparison with the optimal EWMA, CUSUM and GLR schemes
Open Access
- 1 February 2004
- journal article
- Published by Institute of Mathematical Statistics in The Annals of Statistics
- Vol. 32 (1) , 316-339
- https://doi.org/10.1214/aos/1079120139
Abstract
It is known that both the optimal exponentially weighted moving average (EWMA) and cumulative sum (CUSUM) control charts are based on a given reference value $\delta$, which, for the CUSUM chart, is the magnitude of a shift in the mean to be detected quickly. In this paper a generalized EWMA control chart (GEWMA) which does not depend on $\delta$ is proposed for detecting the mean shift. We compare theoretically the GEWMA control chart with the optimal EWMA, CUSUM and the generalized likelihood ratio (GLR) control charts. The results of the comparison in which the in-control average run length approaches infinity show that the GEWMA control chart is better than the optimal EWMA control chart in detecting a mean shift of any size and is also better than the CUSUM control chart in detecting the mean shift which is not in the interval $(0.7842\delta ,1.3798\delta )$. Moreover, the GLR control chart has the best performance in detecting mean shift among the four control charts except when detecting a particular mean shift $\delta,$ when the in-control average run length approaches infinity.
Keywords
This publication has 27 references indexed in Scilit:
- A New SPC Monitoring Method: The ARMA ChartTechnometrics, 2000
- The Maslov integral representation of slowly varying dispersive wavetrains in inhomogeneous moving mediaWave Motion, 2000
- Evaluatiok of optimum weights and average run lenghts in ewma control schemesCommunications in Statistics - Theory and Methods, 1997
- Variable-sampling-interval control charts with sampling at fixed timesIIE Transactions, 1996
- Evaluating properties of variable sampling interval control chartsSequential Analysis, 1995
- Run-Length Distributions of Special-Cause Control Charts for Correlated ProcessesTechnometrics, 1994
- Exponentially weighted moving average control schemes with variable sampling intervalsCommunications in Statistics - Simulation and Computation, 1992
- Optimal Stopping Times for Detecting Changes in DistributionsThe Annals of Statistics, 1986
- Control Chart Tests Based on Geometric Moving AveragesTechnometrics, 1959
- CONTINUOUS INSPECTION SCHEMESBiometrika, 1954