Smart Process Plants Software and Hardware Solutions for Accurate Data and Profitable Operations
by: Miguel J. Bagajewicz, Donald J. Chmielewski
Abstract: An essential guide for process plant engineers–from an introductory tutorial to discussions of new and critical material for the new generation of smart plants: error-free process variable estimation, control, fault detection, instrumentation upgrade and maintenance optimization.Data reconciliation, gross error detection, and instrumentation upgrade are at the center of bias-free accurate estimates of process flowrates, temperatures, and process parameters. The book discusses the value of information, control and fault detection by making connections of these activities to the plant economics. Next it discusses the needed instrumentation to accomplish it. Finally it covers the optimization of preventive maintenance activities, including those of the instrumentation.Smart Process Plants covers introductory mathematical material and contains novel and critical information that is not available in other books. Detailed worked-out examples useful to clarify concepts are included in the book.
Full details
Table of Contents
- A. About the Author
- B. Preface
- 1. Smart Plants
- 2. Measurement Errors
- 3. Variable Classification
- 4. Material Balance Data Reconciliation
- 5. Gross Error Detection
- 6. Equivalency of Gross Errors
- 7. Gross Error Size Elimination and Estimation
- 8. Nonlinear Data Reconciliation
- 9. Dynamic Data Reconciliation
- 10. Accuracy of Estimators
- 11. Economic Value of Accuracy
- 12. Data Reconciliation Practical Issues
- 13. Value of Control Strategies
- 14. Value of Parametric Fault Identification
- 15. Value of Instrumentation Upgrade—Monitoring and Faults Perspectives
- 16. Value of Instrumentation Upgrade—Control Perspective
- 17. Structural Faults and Value of Maintenance
- 18. Maintenance Optimization
- 19. Value and Optimization of Instrument Maintenance
Tools & Media
Expanded Table of Contents
-
A.
About the Author
-
B.
Preface
- 1. Smart Plants
- 2. Measurement Errors
- 3. Variable Classification
- 4. Material Balance Data Reconciliation
- 5. Gross Error Detection
- 6. Equivalency of Gross Errors
- 7. Gross Error Size Elimination and Estimation
- 8. Nonlinear Data Reconciliation
- 9. Dynamic Data Reconciliation
- 10. Accuracy of Estimators
- 11. Economic Value of Accuracy
- 12. Data Reconciliation Practical Issues
-
13.
Value of Control Strategies
- Classic Control
- Model Predictive Control
- The Hierarchy of the Modern Control Architecture
- State-Space Process Modeling
- Disturbance Modeling
- Expected Dynamic Operating Region Characterization
- Constrained Minimum Variance Control
- Connection between CMV Control and MPC
- Control System Value
- Impact of Process and Measurement Biases
- Conclusions
- 14. Value of Parametric Fault Identification
- 15. Value of Instrumentation Upgrade—Monitoring and Faults Perspectives
-
16.
Value of Instrumentation Upgrade—Control Perspective
- 17. Structural Faults and Value of Maintenance
- 18. Maintenance Optimization
- 19. Value and Optimization of Instrument Maintenance
Book Details
Title: Smart Process Plants Software and Hardware Solutions for Accurate Data and Profitable Operations
Publisher: : New York, Chicago, San Francisco, Lisbon, London, Madrid, Mexico City, Milan, New Delhi, San Juan, Seoul, Singapore, Sydney, Toronto
Copyright / Pub. Date: 2010 The McGraw-Hill Companies, Inc.
ISBN: 9780071604710
Authors:
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.
Donald J. Chmielewski is the author of this McGraw-Hill Professional publication.
Description: An essential guide for process plant engineers–from an introductory tutorial to discussions of new and critical material for the new generation of smart plants: error-free process variable estimation, control, fault detection, instrumentation upgrade and maintenance optimization.Data reconciliation, gross error detection, and instrumentation upgrade are at the center of bias-free accurate estimates of process flowrates, temperatures, and process parameters. The book discusses the value of information, control and fault detection by making connections of these activities to the plant economics. Next it discusses the needed instrumentation to accomplish it. Finally it covers the optimization of preventive maintenance activities, including those of the instrumentation.Smart Process Plants covers introductory mathematical material and contains novel and critical information that is not available in other books. Detailed worked-out examples useful to clarify concepts are included in the book.
