CONTROL CHART FOR MULTIVARIATE ATTRIBUTE PROCESSES

Many industrial processes are multivariate in nature since the quality of a product depends on more than one variable. Multivariate control procedures can be used to capture the relationship between the variables and to provide more sensitive control than that provided by the application of univariate control procedures on each variable. Much has been done on the multivariate variable processes, such as embodied in control procedures based on Hotelling's T 2 statistic. However, little work has been done to deal with the control of multivariate attribute processes, which is very important in practical production processes. In this paper, we develop a Shewhart-type control chart to deal with multivariate attribute processes, which is called the multivariate np chart (MNP chart). The control chart uses the weighted sum of the counts of nonconforming units with respect to all the quality characteristics as the plotted statistics. It enhances the efficiency of identifying the critical assignable cause when an ...

[1]  H. I. Patel QUALITY CONTROL METHODS FOR MULTIVARIATE BINOMIAL AND POISSON DISTRIBUTIONS , 1973 .

[2]  John F. MacGregor,et al.  Multivariate SPC charts for monitoring batch processes , 1995 .

[3]  J. E. Jackson Multivariate quality control , 1985 .

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

[5]  Douglas M. Hawkins,et al.  Regression Adjustment for Variables in Multivariate Quality Control , 1993 .

[6]  Patrick D. Bourke,et al.  Detecting a shift in fraction nonconforming using runlength control charts with 100% inspection , 1991 .

[7]  S. J. Wierda Multivariate statistical process control—recent results and directions for future research , 1994 .

[8]  Thomas P. Ryan,et al.  Statistical methods for quality improvement , 1989 .

[9]  Richard K. Miller,et al.  Automated Inspection and Quality Assurance , 1989 .

[10]  William H. Woodall,et al.  A review and analysis of cause-selecting control charts , 1993 .

[11]  Eli A. Glushkovsky ‘On-line’ G-control chart for attribute data , 1994 .

[12]  George C. Runger,et al.  Comparison of multivariate CUSUM charts , 1990 .

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

[14]  Theodora Kourti,et al.  Multivariate SPC Methods for Process and Product Monitoring , 1996 .

[15]  G. Runger Multivariate statistical process control for autocorrelated processes , 1996 .

[16]  Thong Ngee Goh,et al.  Some procedures for decision making in controlling high yield processes , 1992 .

[17]  T. M. Margavio,et al.  A comparison of multivariate moving average control charts for the process mean , 1995 .

[18]  J. Healy A note on multivariate CUSUM procedures , 1987 .

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

[20]  James C. Benneyan,et al.  Statistical Control Charts Based on a Geometric Distribution , 1992 .

[21]  R. Crosier Multivariate generalizations of cumulative sum quality-control schemes , 1988 .

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

[23]  J. Edward Jackson,et al.  A User's Guide to Principal Components. , 1991 .

[24]  W. Woodall,et al.  Multivariate CUSUM Quality- Control Procedures , 1985 .

[25]  Francisco Aparisi,et al.  Hotelling's T2 control chart with adaptive sample sizes , 1996 .

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

[27]  Douglas C. Montgomery,et al.  Some Statistical Process Control Methods for Autocorrelated Data , 1991 .