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Multivariate Statistical Process Control with Industrial Application (ASA-SIAM Series on Statistics and Applied Probability 9)
 
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Multivariate Statistical Process Control with Industrial Application (ASA-SIAM Series on Statistics and Applied Probability 9) [Hardcover]

Robert L. Mason (Author), John C. Young (Author)

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Book Description

December 4, 2001 0898714966 978-0898714968 1st
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.

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Book Description

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.

About the Author

Robert L. Mason is a Staff Analyst at Southwest Research Institute in San Antonio, Texas. He is a fellow of the American Statistical Association and also a fellow of the American Society for Quality. He serves on the editorial boards of the ASA-SIAM Series on Statistics and Applied Probability and the Journal of Quality Technology.

John C. Young is Professor of Statistics at McNeese State University in Lake Charles, Louisiana. He is also President and Co-owner of InControl Technologies, Inc., a consulting firm that specializes in multivariate analysis with emphasis in multivariate statistical process control.


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