Focusing on continuous, multivariate processes, this book introduces statistical methods and modeling techniques for process monitoring, process and controller performance evaluation, and fault diagnosis. It covers empirical modeling development techniques, modeling process signals for trend analysis, and sensor failure detection and diagnosis.

Focusing on continuous, multivariate processes, Chemical Process Performance Evaluation introduces statistical methods and modeling techniques for process monitoring, process and controller performance evaluation, and fault diagnosis. The book covers empirical modeling development techniques, modeling process signals for trend analysis, sensor failure detection and diagnosis, controller performance assessment, process performance evaluation, and data analysis techniques for web and sheet processes. Balancing practice and theory, the book integrates several techniques to facilitate practical applications. Case studies illustrate the implementation of methods presented throughout.

"Most texts that attempt to combine SPC or SPM (statistical process monitoring) with automated control methods fail to incorporate multivariate methods as well. This text does an excellent job of covering all the bases in that regard . . . I highly recommend this text for chemical engineers and statisticians interested in learning how statistical methods can be integrated with process control methods." - Dean V. Neubauer, Corning Inc., in Technometrics, February 2008, Vol. 50, No. 1