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Smart Process Plants: Software and Hardware Solutions for Accurate Data and Profitable Operations

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Smart Process Plants: Software and Hardware Solutions for Accurate Data and Profitable Operations Cover

 

Synopses & Reviews

Publisher Comments:

A Detailed Guide to the New Generation of Smart Process PlantsMaximize 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 errorsVariable classification and canonical representationLinear, nonlinear, and dynamic data reconciliationGross error detection, equivalency, size elimination, and estimationAccuracy of estimatorsValue of accuracy, control strategies, parametric fault identification, and instrumentation upgradeMaintenance optimization

Synopsis:

An essential guide for process plant engineers--from an introductory tutorial to discussions of new and critical material, including data accuracy and error-free process

Data reconciliation, gross error detection, and instrumentation upgrade are at the center of bias-free accurate estimates of process flowrates, temperatures, and process parameters. This book utilizes a less mathematically intimidating approach in order to educate process plant operation management as well as process engineers.

Smart Process Plants covers introductory mathematical material and contains novel and critical information that is not available in other books. Software for data reconciliation practice will be available for download, and worked-out examples and exercises are included in the book.

Synopsis:

Ch 1. Smart Plants

Ch 2. Measurement Errors

Ch 3. Variable Classification

Ch 4. Linear Data Reconciliation

Ch 5. Gross Error Detection

Ch 6. Equivalencies of Gross Errors

Ch 7. Gross Error Size Estimation

Ch 8. Nonlinear Data reconciliation

Ch 9. Dynamic Data Reconciliation

Ch 10. Accuracy

Ch 11. Value of Accuracy

Ch 12. Practical Issues in the implementation of data reconciliation plant wide

Ch 13. Value of Control

Ch 14. Value of Fault detection

Ch 15. Instrumentation Design and Upgrade

Ch 16. Value of Instrumentation Upgrade-Control Perspective

Ch 17. Maintenance

Ch 18. Maintenance Optimization

Ch 19. Instrument Maintenance

Professor Miguel J. Bagajewiczis 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

Chapter 1. Smart Plants; Chapter 2. Measurement Errors; Chapter 3. Variable Classification; Chapter 4. Material Balance Data Reconciliation; Chapter 5. Gross Error Detection; Chapter 6. Equivalency of Gross Errors; Chapter 7. Gross Error Size Elimination and Estimation; Chapter 8. Nonlinear Data Reconciliation; Chapter 9. Dynamic Data Reconciliation; Chapter 10. Accuracy of Estimators; Chapter 11. Ecomimic VEconomic Accuracy; Chapter 12. Data Reconciliation Practical Issues; Chapter 13. Value of Control Strategies; Chapter 14. Value of Parametric Fault Identification; Chapter 15. Value of Instrumentation Upgrade--Monitoring and Faults Perspectives; Chapter 16. Value of Instrumentation Upgrade--Control Perspective; Chapter 17. Structural Faults and Value of Maintenance; Chapter 18. Maintenance Optimization; Chapter 19. Value and Optimization of Instrument Maintenance; Index

Product Details

ISBN:
9780071604727
Publisher:
McGraw-Hill Professional
Subject:
Technology & Engineering : Industrial Engineering
Author:
Chmielewski, Donald J.
Author:
Bagajewicz, Miguel J.
Author:
Tanth, DuyQuang Nguyen
Subject:
Industrial engineering
Subject:
Mathematical Analysis
Subject:
Probability & Statistics - General
Subject:
Process control
Subject:
Process control -- Data processing.
Subject:
Industrial and Control Engineering-General
Subject:
Chemistry-Chemical Engineering
Subject:
main_subject
Subject:
all_subjects
Publication Date:
November 2009
Binding:
eBooks
Language:
English
Pages:
464

Related Subjects

Business » Human Resource Management
Business » Project Management
Engineering » Engineering » General Engineering
Engineering » Industrial and Control Engineering » General
Reference » Science Reference » Technology
Science and Mathematics » Chemistry » Chemical Engineering
Science and Mathematics » Chemistry » General
Science and Mathematics » Mathematics » Analysis General
Science and Mathematics » Mathematics » Probability and Statistics » General

Smart Process Plants: Software and Hardware Solutions for Accurate Data and Profitable Operations
0 stars - 0 reviews
$ In Stock
Product details 464 pages McGraw-Hill - English 9780071604727 Reviews:
"Synopsis" by , An essential guide for process plant engineers--from an introductory tutorial to discussions of new and critical material, including data accuracy and error-free process

Data reconciliation, gross error detection, and instrumentation upgrade are at the center of bias-free accurate estimates of process flowrates, temperatures, and process parameters. This book utilizes a less mathematically intimidating approach in order to educate process plant operation management as well as process engineers.

Smart Process Plants covers introductory mathematical material and contains novel and critical information that is not available in other books. Software for data reconciliation practice will be available for download, and worked-out examples and exercises are included in the book.

"Synopsis" by , Ch 1. Smart Plants

Ch 2. Measurement Errors

Ch 3. Variable Classification

Ch 4. Linear Data Reconciliation

Ch 5. Gross Error Detection

Ch 6. Equivalencies of Gross Errors

Ch 7. Gross Error Size Estimation

Ch 8. Nonlinear Data reconciliation

Ch 9. Dynamic Data Reconciliation

Ch 10. Accuracy

Ch 11. Value of Accuracy

Ch 12. Practical Issues in the implementation of data reconciliation plant wide

Ch 13. Value of Control

Ch 14. Value of Fault detection

Ch 15. Instrumentation Design and Upgrade

Ch 16. Value of Instrumentation Upgrade-Control Perspective

Ch 17. Maintenance

Ch 18. Maintenance Optimization

Ch 19. Instrument Maintenance

Professor Miguel J. Bagajewiczis 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.

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