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CITATION

Bagajewicz, Miguel. Smart Process Plants: Software and Hardware Solutions for Accurate Data and Profitable Operations. US: McGraw-Hill Professional, 2009.

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

Authors: Miguel Bagajewicz

Published:  November 2009

eISBN: 9780071604727 0071604723 | ISBN: 9780071604710
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  • Contents
  • Preface
  • 1 Smart Plants
  • Our Vision
  • Value of Information
  • Book Focus and Contents
  • References
  • 2 Measurement Errors
  • Range and Span
  • Precision
  • Origin of Fluctuations
  • Systematic Error (Bias)
  • Outliers
  • Accuracy
  • Calibration Curves
  • Hysteresis and Dead Band
  • Guide to the Expression of Uncertainty in Measurement
  • References
  • 3 Variable Classification
  • Linear Model
  • Observability
  • Redundancy
  • Hardware Redundancy
  • Quantification of Observability and Redundancy
  • Estimability
  • Degree of Observability of Variables
  • Degree of Redundancy of Variables
  • Degree of Estimability of Variables
  • Canonical Representation
  • The General Case
  • References
  • 4 Material Balance Data Reconciliation
  • Determination of the Measurement Vector
  • Precision of the Estimates
  • Variance of Observable Quantities
  • Method to Avoid the Classification Step
  • References
  • 5 Gross Error Detection
  • Gross Error Handling
  • Smearing
  • Tests for Gross Errors
  • Hypothesis Testing
  • Type I and Type II Errors and the Power of a Test
  • Global Test
  • Nodal Test
  • Maximum Power Nodal Test
  • Measurement Test
  • Maximum Power Measurement Test
  • Generalized Likelihood Ratio
  • Principal Component Test
  • Multiple Gross Errors and Gross Error Elimination
  • Serial Elimination Strategy Based on the Global Test
  • Serial Elimination Based on the Measurement Test
  • Failures of Tests
  • References
  • 6 Equivalency of Gross Errors
  • Definition
  • Practical Consequences
  • Cardinality of Equivalent Sets
  • Basic Subset of an Equivalent Set
  • Determination of Equivalent Sets
  • Practical Consequence
  • Degeneracy
  • Quasi-Degeneracy
  • Quasi-Equivalency
  • Detection of Leaks
  • Practical Approach to Equivalency
  • References
  • 7 Gross Error Size Elimination and Estimation
  • The Compensation Model
  • Serial Identification with Collective Compensation Strategy (SICC)
  • The Unbiased Estimation Model (UBET)
  • Conversion between Equivalent Sets
  • References
  • 8 Nonlinear Data Reconciliation
  • Component Balances
  • Splitters
  • Number of Components
  • Measurement Pattern
  • Energy Balances
  • Heat Exchangers
  • Full Nonlinear Systems
  • Gross Error Detection in Nonlinear Systems
  • Parameter Estimation
  • References
  • 9 Dynamic Data Reconciliation
  • Filtering
  • Recursive Filters
  • Linear Estimators
  • Discrete Kalman Filter
  • Quasi-Steady State Estimator
  • A Balance-Based Quasi-Steady State Estimator
  • Difference Estimators
  • Integral Approach
  • Nonlinear Case
  • Gross Error Detection
  • References
  • 10 Accuracy of Estimators
  • Accuracy of Measurements
  • Induced Bias
  • Accuracy of Estimators
  • Maximum Undetected Induced Bias
  • Maximum Power Measurement Test-Based Software Accuracy
  • Graphical Representation of Undetected Biases
  • Effect of Equivalency of Errors
  • Stochastic Software Accuracy
  • Monte Carlo Sampling
  • Instantaneous Testing
  • Periodic Testing
  • References
  • 11 Economic Value of Accuracy
  • Value of Precision
  • Value of Accuracy
  • Probabilities
  • Trade-Off between Value and Cost
  • References
  • 12 Data Reconciliation Practical Issues
  • Data Preprocessing
  • Use of Filters
  • Steady-State Recognition and Variance
  • Variance Estimation
  • Steady-State Detection
  • Ratio Test
  • Tanks and Steady-State Data Reconciliation
  • Use of Dynamic Data in Steady-State Reconcilers
  • Random Error Distributions
  • Multiple Measurements of the Same Variable
  • Excessive Number of Gross Errors
  • References
  • 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
  • References
  • 14 Value of Parametric Fault Identification
  • Introduction
  • Fault Classification
  • Fault Detection and Diagnosis Techniques
  • Fault Observability
  • Single Fault Resolution
  • Multiple Fault Resolution
  • Value of Fault Detection
  • References
  • 15 Value of Instrumentation Upgrade—Monitoring and Faults Perspectives
  • Cost-Optimal Instrumentation Design
  • Cost-Optimal Design
  • Cost-Optimal Design for Precision or Accuracy
  • Tree Search Procedure for the Cost-Optimal Formulation
  • Branching Criteria
  • Cost-Optimal Design for Parametric Faults
  • Integrated Cost-Optimal Design
  • Value-Optimal Instrumentation Design
  • References
  • 16 Value of Instrumentation Upgrade—Control Perspective
  • References
  • 17 Structural Faults and Value of Maintenance
  • Maintenance
  • Maintenance Policies
  • Reliability, Failure Rate, and Mean Time to Failure
  • Failure Density Distributions
  • Exponential Distribution
  • Weibull Distribution
  • Normal Distribution
  • Maintenance Models
  • Renewal Processes
  • Markov Processes
  • Discrete Time Markov Models
  • Monte Carlo Simulation
  • Maintenance Policy and Decision Variables
  • Interfering/Noninterfering Units
  • Input Data
  • Spare Parts Inventory
  • Labor Assignment
  • Imperfect Maintenance
  • Maintenance Rules
  • Monte Carlo Simulation Procedure
  • Advantages and Limitations
  • Renewal Process
  • Markov Process
  • Monte Carlo Simulation
  • References
  • 18 Maintenance Optimization
  • Components of Maintenance Optimization
  • Renewal Process–Based Models
  • Markov-Based Model
  • Monte Carlo–Based Models Using Genetic Algorithms
  • References
  • 19 Value and Optimization of Instrument Maintenance
  • Financial Loss Evaluation
  • References
  • Index