Smart Process Plants: Software and Hardware Solutions for Accurate Data and Profitable Operations: Data Reconciliation, Gross Error Detection, and Instrumentation Upgrade

A Detailed Guide to the New Generation of Smart Process Plants

Maximize plant profitability by minimizing operating costs. Smart Process Plants addresses measurements and the data they generate, error–free process variable estimation, control, fault detection, instrumentation upgrade, and maintenance optimization, and then connects these activities to plant economics. Methods for calculating the value of the information produced are included. The book discusses optimal instrumentation type, quality, precision, and location along with preventive maintenance techniques. Practical examples throughout the book demonstrate how to perform essential calculations.

Smart Process Plants covers:

• Measurement instrument performance and measurement errors
• Variable classification and canonical representation
• Linear, nonlinear, and dynamic data reconciliation
• Gross error detection, equivalency, size elimination, and estimation
• Accuracy of estimators
• Value of accuracy, control strategies, parametric fault identification, and instrumentation upgrade
• Maintenance optimization

Professor Miguel J. Bagajewicz is the Sam Wilson Professor of Chemical Engineering at the University of Oklahoma. His research is in the fields of design, operation, simulation, and optimization of process plants and product design. In addition, Bagajewicz specializes in financial risk, environmentally benign processes, and micro–economics, as applied to product design.