Mason R.L., Young J.C. Multivariate statistical process control with industrial applications

Philadelphia: SIAM, 2002. — 277 p.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.
Specifically devoted to the T2 methodology, Multivariate Statistical Process Control with Industrial Applications is the only book available that concisely and thoroughly presents such topics as how to construct a historical data set; how to check the necessary assumptions used with this procedure; how to chart the T2 statistic; how to interpret its signals; how to use the chart in the presence of autocorrelated data; and how to apply the procedure to batch processes. The book comes with a CD-ROM containing a 90-day demonstration version of the QualStat multivariate SPC software specifically designed for the application of T2 control procedures. The CD-ROM is compatible with Windows 95, Windows 98, Windows Me Millennium Edition, and Windows NT operating systems.
Audience Analysts seeking to use Hotelling's T2 as a control statistic for a multivariate industrial process will find this consolidated reference invaluable. The book will show readers how to establish and utilize the multivariate control procedure based on Hotelling's T2 statistic and to apply it to an industrial process. Readers should be familiar with univariate control chart construction and monitoring procedures, but need not be informed about the application of multivariate control procedures based on the T2 statistic.Introduction to the T2 Statistic
Basic Concepts about the T2 Statistic
Checking Assumptions for Using a T2 Statistic
Construction of Historical Data Set
Charting the T2 Statistic in Phase I
Charting the T2 Statistic in Phase II
Interpretation of T2 Signals for Two Variables
Interpretation of T2 Signals for the General Case
Improving the Sensitivity of the T2 Statistic
Autocorrelation in T2 Control Charts
The T2 Statistic and Batch Processes
Distribution Tables