Model 7.9 Matlab Code to Generate the Best ANN Model References Appendix 7.1 Matlab Code to Generate the Best ANN Model
12 8 Optimization of Industrial Processes and Process Equipment 8.1 Meaning of Optimization in an Industrial Context 8.2 How Can Optimization Increase Profit? 8.3 Types of Optimization 8.4 Different Methods of Optimization 8.5 Brief Historical Perspective of Heuristic‐based Non‐traditional Optimization Techniques 8.6 Genetic Algorithm 8.7 Differential Evolution 8.8 Simulated Annealing 8.9 Case Study: Application of the Genetic Algorithm Technique to Optimize the Industrial Ethylene Oxide Reactor 8.10 Strategy to Utilize Data‐Driven Modeling and Optimization Techniques to Solve Various Industrial Problems and Increase Profit References Appendix 8.1 Matlab Code for GA Optimization of an EO Reactor Case Study
13 9 Process Monitoring 9.1 Need for Advance Process Monitoring 9.2 Current Approaches to Process Monitoring and Diagnosis 9.3 Development of an Online Intelligent Monitoring System 9.4 Development of KPI‐Based Process Monitoring 9.5 Development of a Cause and Effect‐Based Monitoring System 9.6 Development of Potential Opportunity‐Based Dash Board 9.7 Development of Business Intelligent Dashboards 9.8 Development of Process Monitoring System Based on Principal Component Analysis 9.9 Case Study for Operational State Identification and Monitoring Using PCA References
14 10 Fault Diagnosis 10.1 Challenges to the Chemical Industry 10.2 What is Fault Diagnosis? 10.3 Benefit of a Fault Diagnosis System 10.4 Decreasing Downtime Through a Fault Diagnosis Type Data Analytics 10.5 User Perspective to Make an Effective Fault Diagnosis System 10.6 How Are Fault Diagnosis Systems Made? 10.7 A Case Study to Build a Robust Fault Diagnosis System 10.8 Building an ANN Model for Fault Diagnosis of an EO Reactor 10.9 Integrated Robust Fault Diagnosis System 10.10 Advantages of a Fault Diagnosis System References
15 11 Optimization of an Existing Distillation Column 11.1 Strategy to Optimize the Running Distillation Column 11.2 Increase the Capacity of a Running Distillation Column 11.3 Capacity Diagram 11.4 Capacity Limitations of Distillation Columns 11.5 Vapour Handling Limitations 11.6 Liquid Handling Limitations 11.7 Other Limitations and Considerations 11.8 Understanding the Stable Operation Zone (Zhu, 2013) 11.9 Case Study to Develop a Capacity Diagram References
16 12 New Design Methodology 12.1 Need for New Design Methodology 12.2 Case Study of the New Design Methodology for a Distillation Column 12.3 New Intelligent Methodology for Designing a Distillation Column 12.4 Problem Description of the Case Study 12.5 Solution Procedure Using the New Design Methodology 12.6 Calculations of the Total Cost 12.7 Search Optimization Variables 12.8 Operational and Hydraulic Constraints 12.9 Particle Swarm Optimization 12.10 Simulation and PSO Implementation 12.11 Results and Analysis 12.12 Advantages of PSO 12.13 Advantages of New Methodology over the Traditional Approach (Lahiri, 2014) 12.14 Conclusion Nomenclature References
17 13 Genetic Programing for Modeling of Industrial Reactors 13.1 Potential Impact of Reactor Optimization on Overall Profit 13.2 Poor Knowledge of Reaction Kinetics of Industrial Reactors