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Balancing theory and practice, Chemical Process Performance Evaluation reviews techniques for monitoring a single variable and discusses the limits of classical techniques. This book provides statistical methods for evaluating multivariable processes and fault diagnosis. It presents empirical model development techniques and statistical process monitoring methods that use such techniques. Emphasis is placed on using wavelets, fuzzy triangular episodes, and hidden Markov models, and modeling process signals for trend analysis. Additional coverage includes sensor failure detection and diagnosis, controller performance assessment, process performance evaluation, and web and sheet processes.