Multivariate Statistical Process Control with Industrial Applications

This applied, self-contained text provides detailed coverage of the practical aspects of multivariate statistical process control (MVSPC) based on the application of Hotelling's T2 statistic. MVSPC is the application of multivariate statistical techniques to improve the quality and productivity of an industrial process. The authors, leading researchers in this area who have developed major software for this type of charting procedure, provide valuable insight into the T2 statistic. Intentionally including only a minimal amount of theory, they lead readers through the construction and monitoring phases of the T2 control statistic using numerous industrial examples taken primarily from the chemical and power industries. These examples are applied to the construction of historical data sets to serve as a point of reference for the control procedure and are also applied to the monitoring phase, where emphasis is placed on signal location and interpretation in terms of the process variables.

Preface; 1. Introduction to the T2 Statistic; 2. Basic Concepts about the T2 Statistic; 3. Checking Assumptions for Using a T2 Statistic; 4. Construction of Historical Data Set; 5. Charting the T2 Statistic in Phase I; 6. Charting the T2 Statistic in Phase II; 7. Interpretation of T2 Signals for Two Variables; 8. Interpretation of T2 Signals for the General Case; 9. Improving the Sensitivity of the T2 Statistic; 10. Autocorrelation in T2 Control Charts; 11 The T2 Statistic and Batch Processes; Appendix. Distribution Tables; Bibliography; Index.

Detailed coverage of the practical aspects of multivariate statistical process control (MVSPC) based on the application of Hotelling's T2 statistic. MVSPC is the application of multivariate statistical techniques to improve the quality and productivity of an industrial process. Provides valuable insight into the T2 statistic.