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
1101366567
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
135.0 In Stock
Smart Process Plants: Software and Hardware Solutions for Accurate Data and Profitable Operations: Data Reconciliation, Gross Error Detection, and Instrumentation Upgrade

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

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

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

by Miguel J. Bagajewicz

eBook

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Overview

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

Product Details

ISBN-13: 9780071604727
Publisher: McGraw-Hill Education
Publication date: 09/22/2009
Sold by: Barnes & Noble
Format: eBook
Pages: 300
File size: 19 MB
Note: This product may take a few minutes to download.

About the Author

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.

Table of Contents

Ch 1. Objectives of Monitoring. Data Reconciliation
Ch 2. Measurement Errors
Ch 3. Variable Classification
Ch 4. Material Balance Data Reconciliation
Ch 5. Gross Error Detection
Ch 6. Multiple Gross Error Identification
Ch 7. Equivalencies of Gross Errors
Ch 8. Gross Errors Size Estimation
Ch 9. Component and Energy Data Reconciliation
Ch 10. Dynamic Data Reconciliation
Ch 11. Accuracy
Ch 12. Value of Information
Ch 13. Practical Issues in the Implementation of Data Reconciliation Plant Wide and Enterprise Wide
Ch 14. Instrumentation Design and Upgrade
Ch 15. Nonlinear Systems
Ch 16. Maintenance
Ch 17. Case Studies
Appendix: Review of Materices and Statistics
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