Optimal Design of a CUSUM Chart for a Mean Shift of Unknown Size

The cumulative sum (CUSUM) control chart is one of the most popular methods used to detect a process mean shift. When one specific size of the mean shift is assumed, the CUSUM chart can be optimally designed in terms of average run length (ARL). In practice, however, the size of the mean shift is usually unknown, and the CUSUM chart can perform poorly when the actual size of the mean shift is significantly different from the assumed size. In this paper, we assign a probability distribution to the size of the mean shift to represent the lack of knowledge of the shift size. We use an ARL-based performance measure, called expected weighted run length (EWRL), and propose a method to optimally design a CUSUM chart based on EWRL. This method can be easily extended to other CUSUM-based control charts, such as weighted CUSUM and multi-CUSUM charts proposed in the literature. The numerical results show that the CUSUM or the CUSUM-based chart can be improved by our proposed method in terms of EWRL.

[1]  G. Moustakides Optimal stopping times for detecting changes in distributions , 1986 .

[2]  I. Eisenberger,et al.  Detection of Failure Rate Increases , 1971 .

[3]  Harrison M. Wadsworth,et al.  Journal of Quality Technology, The , 2005 .

[4]  Wei Jiang,et al.  A Weighted CUSUM Chart for Detecting Patterned Mean Shifts , 2008 .

[5]  Wei Jiang,et al.  A Markov Chain Model for the Adaptive CUSUM Control Chart , 2006 .

[6]  William H. Woodall,et al.  Introduction to Statistical Quality Control, Fifth Edition , 2005 .

[7]  W. Cheney,et al.  Numerical analysis: mathematics of scientific computing (2nd ed) , 1991 .

[8]  D. Siegmund Sequential Analysis: Tests and Confidence Intervals , 1985 .

[9]  D. A. Evans,et al.  An approach to the probability distribution of cusum run length , 1972 .

[10]  E. S. Page CONTINUOUS INSPECTION SCHEMES , 1954 .

[11]  Marion R. Reynolds,et al.  An Evaluation of a GLR Control Chart for Monitoring the Process Mean , 2010 .

[12]  Dong Han,et al.  A CUSUM CHART WITH LOCAL SIGNAL AMPLIFICATION FOR DETECTING A RANGE OF UNKNOWN SHIFTS , 2007 .

[13]  赵仪,et al.  Dual CUSUM control schemes for detecting a range of mean shifts , 2005 .

[14]  R. Khan,et al.  Sequential Tests of Statistical Hypotheses. , 1972 .

[15]  Ross Sparks,et al.  CUSUM Charts for Signalling Varying Location Shifts , 2000 .

[16]  James M. Lucas,et al.  Combined Shewhart-CUSUM Quality Control Schemes , 1982 .

[17]  D. Siegmund,et al.  Using the Generalized Likelihood Ratio Statistic for Sequential Detection of a Change-Point , 1995 .

[18]  J. Douglas Faires,et al.  Numerical Analysis , 1981 .

[19]  Zhang Wu,et al.  Optimization design of control charts based on Taguchi's loss function and random process shifts , 2004 .

[20]  Y. K. Chen,et al.  Design of EWMA and CUSUM control charts subject to random shift sizes and quality impacts , 2007 .

[21]  Wei Jiang,et al.  Adaptive CUSUM procedures with EWMA-based shift estimators , 2008 .

[22]  Petri Helo,et al.  Optimization design of a CUSUM control chart based on taguchi’s loss function , 2008 .

[23]  Richard A. Johnson,et al.  The Influence of Reference Values and Estimated Variance on the Arl of Cusum Tests , 1975 .

[24]  Jianjun Shi,et al.  The GLRT for statistical process control of autocorrelated processes , 1999 .