Interpreting out-of-control signals of MEWMA control charts employing neural networks

Multivariate quality control charts show some advantages to monitor several variables in comparison with the simultaneous use of univariate charts. Nevertheless, there are some disadvantages when multivariate schemes are employed. The main problem is how to interpret the out-of-control signal of a multivariate chart. For example, in the case of control charts designed to monitor the mean vector, the chart signals showing that it must be accepted that there is a shift in the vector, but no indication is given about the variables that have produced this shift. The MEWMA quality control chart is a very powerful scheme to detect small shifts in the mean vector. There are no previous specific works about the interpretation of the out-of-control signal of this chart. In this paper neural networks are designed to interpret the out-of-control signal of the MEWMA chart, and the percentage of correct classifications is studied for different cases. The utilization of this neural network in the industry is very easy, thanks to the developed software.

[1]  John C. Young,et al.  A Practical Approach for Interpreting Multivariate T2 Control Chart Signals , 1997 .

[2]  Ali A. Houshmand,et al.  SIMULTANEOUS REPRESENTATION OF MULTIVARIATE AND CORRESPONDING UNIVARIATE X¯ CHARTS USING LINE-GRAPH , 1995 .

[3]  Douglas C. Montgomery,et al.  Introduction to Statistical Quality Control , 1986 .

[4]  Loon Ching Tang,et al.  QUALITY NOTES: Simultaneous monitoring of univariate and multivariate SPC information using boxplots , 1998 .

[5]  Linda W. Blazek,et al.  Displaying Multivariate Data Using Polyplots , 1987 .

[6]  Francisco Aparisi,et al.  Techniques to interpret T 2 control chart signals , 2006 .

[7]  Arthur B. Yeh,et al.  A multivariate exponentially weighted moving average control chart for monitoring process variability , 2003 .

[8]  Douglas C. Montgomery,et al.  A review of multivariate control charts , 1995 .

[9]  George C. Runger,et al.  Designing a Multivariate EWMA Control Chart , 1997 .

[10]  Charles W. Champ,et al.  A multivariate exponentially weighted moving average control chart , 1992 .

[11]  Nola D. Tracy,et al.  Decomposition of T2 for Multivariate Control Chart Interpretation , 1995 .

[12]  W. T. Tucker,et al.  Identification of out of control quality characteristics in a multivariate manufacturing environment , 1991 .

[13]  David C. Hoaglin,et al.  Use of Boxplots for Process Evaluation , 1987 .

[14]  Yoav Benjamini,et al.  Multivariate Profile Charts for Statistical Process Control , 1994 .

[15]  D. Montgomery,et al.  Contributors to a multivariate statistical process control chart signal , 1996 .