This book addresses the topic of integrated digitization of plants on an objective basis and in a holistic manner by sharing data, applying analytics tools and integrating workflows via pertinent examples from industry. It begins with an evaluation of current performance management practices and an overview of the need for a "Connected Plant" via digitalization followed by sections on "Connected Assets: Improve Reliability and Utilization," "Connected Processes: Optimize Performance and Economic Margin " and "Connected People: Digitalizing the Workforce and Workflows and Developing Ownership and Digital Culture," then culminating in a final section entitled "Putting All Together Into an Intelligent Digital Twin Platform for Smart Operations and Demonstrated by Application cases."
Table of Contents
Preface xiii
Acknowledgments xvii
Part 1 Challenges and Opportunities For Digitalization 1
1 Challenges for Operation Excellence 3
1.1 Introduction 3
1.2 Operation Activities in a Process Plant 4
1.3 The Major Challenges Facing the Industries 5
1.4 The Methodology of Connected Plant 11
1.5 Digitalization Enabling Connected Plant 12
1.6 What is the Digitalization Journey? 18
1.7 Overview of the Book Structure 19
References 21
2 Mission of Connected Plant 23
2.1 What is Connected Plant? 23
2.2 Major Functions of Connected Plant 24
2.3 Digital Twins: The Core of Connected Plant 27
2.4 Conclusions 32
References 33
3 Data Analytics for Operation Excellence 35
3.1 Introduction 35
3.2 Process Data Overview: Characteristics and Attributes 37
3.3 Unique Attributes of Process Data Analytics 39
3.4 Model Types and Characteristics 40
3.5 First Principle Modeling and its Characteristics 42
3.6 Statistic Modeling and its Characteristics 45
3.7 Optimization Models 47
3.8 Artificial Intelligence (AI) and Machine Learning (ML) Models 50
3.9 Put All Together: Digital Twin as a Data Science Platform 55
References 59
Part 2 Model Thinking For Smart Operations 63
4 Statistics Basics 65
4.1 Introduction 65
4.2 Normal Distribution 65
4.3 Conditional Probability 72
4.4 Bayes’ Probability 73
4.5 Statistic Tests 75
References 84
5 Advanced Statistic Modeling 85
5.1 Introduction 85
5.2 Distribution Models 85
5.3 Correlation Models 94
5.4 Advanced Modeling Techniques 101
5.5 Data Mining 106
5.6 Summary 107
References 107
6 Rigorous Process Modeling 109
6.1 Introduction 109
6.2 Reaction Kinetic Modeling 110
6.3 Reactor Types and Modeling 126
6.4 Integrated Kinetics and Reactor Modeling 131
6.5 Catalyst Deactivation Root Causes and Modeling 135
6.6 Distillation Modeling 136
6.7 Process System Modeling and Simulation 138
6.8 Separation Technology Overview 142
References 144
7 Linear Optimization Modeling 147
7.1 Introduction 147
7.2 Linear Optimization for Planning 148
7.3 How to Deal with Nonlinear Terms? 151
7.4 Delta Vector as Linear Approximation of Nonlinear Yield Models 154
7.5 Successive Linear Programing (SLP) Approach 159
References 160
8 Nonlinear Optimization Modeling 161
8.1 Introduction 161
8.2 Successive Quadratic Programming (SQP) Approach 162
8.3 Local Versus Global Optimum 162
8.4 Optimality Conditions 166
8.5 Nonlinear Process Optimization Model 167
8.6 Stochastic Programming 171
8.7 Simulation-Based Optimization 178
8.8 A Case Study for Process Optimization 180
8.9 Concluding Remarks 188
References 190
9 Process Control and APC Modeling 193
9.1 Introduction 193
9.2 Process Modeling in Control 194
9.3 Regulatory Control: Managing Individual Variables 207
9.4 PID Controller Modeling 211
9.5 Advanced Process Control (APC) 221
References 233
10 AI and Machine Learning Modeling 235
Amit Gupta and Frank (Xin X.) Zhu
10.1 Introduction 235
10.2 Artificial Neural Networks 235
10.3 Key Concept in ML: Perceptron 238
10.4 Machine Learning 242
10.5 Ml Applications in the Process Industry 246
References 248
Part 3 Connected Plant For Smart Operations 251
11 Connected Metering and Measurements 253
Martin Bragg
11.1 Introduction 253
11.2 Review of Metering Devices 254
11.3 Connected Metering 258
11.4 Positive-Unexpected Consequences of the Digital Economy 267
11.5 The Outlook for Connected Metering 269
11.6 Conclusions 273
References 274
12 Connected Asset and Safety Management 275
Frank (Xin X.) Zhu and Tony Downes
12.1 Introduction 275
12.2 Review of Different Maintenance Strategies 276
12.3 The Concept of Operating Windows 280
12.4 The Major Gaps in Current Asset Management 283
12.5 Digitalized Asset Management 284
12.6 Process Safety Management 290
12.7 Case Study: APM Drives Capacity Improvement 299
Reference 301
13 Integrated Production Planning and Process Control 303
13.1 Introduction 303
13.2 Current Practice in Site-Wide Optimization and Control 304
13.3 Simultaneous Approach for Site-Wide Optimization and Control 304
13.4 General Decomposition Strategy 309
13.5 MPC-Based Integration Approach 314
13.6 Rigorous Model-Based Integration Approach 322
13.7 Comparison Between the MPC and Rigorous Model-Based Approaches 324
References 325
14 Digitalizing the Energy Management 327
14.1 Introduction 327
14.2 The Concept of Energy Intensity 328
14.3 Energy Benchmarking for Processes 337
14.4 The Concept of Key Indicators 340
14.5 Set Up Targets for Key Indicators 346
14.6 Economic Evaluation for Key Indicators 350
14.7 Site-Wide Energy Management Strategy 354
14.8 Digital Twin for Energy Management 360
14.9 Establishing Energy Management System 361
References 365
15 Integrating the Workflows 367
Frank (Xin X.) Zhu and Joe Ritchie
15.1 Introduction 367
15.2 Key Elements of Industrial Supply Chain 368
15.3 Little Integration of Supply Chain Work Processes 381
15.4 Gaps Existing in Current Supply Chain Management 382
15.5 Integrated Work Process for Supply Chain Management 383
15.6 Supply Chain Digital Twin: One Platform for Workflow Integration and Automation 385
15.7 Integration of Engineering Models with Supply Chain
Digital Twin 387
References 388
16 Digitalizing the Workforce 389
Rohan McAdam
16.1 Introduction 389
16.2 Enabling the Workforce 390
16.3 Empowering the Workforce 398
16.4 Digitalization Challenges 410
16.5 Summary 416
References 416
Part 4 Digital Solutions For Smart Operations 419
17 Honeywell Forge: The Platform for Connected Plant 421
Matt Burd and Frank (Xin X.) Zhu
17.1 Honeywell Forge: A Digital Platform for Connected Plant 421
17.2 IIoT for Data Infrastructure 421
17.3 How It Works? 423
17.4 Intelligent Models Behind Digital Twins in Honeywell Forge 429
17.5 Cybersecurity 434
Reference 436
18 Digital Reediness Assessment and Six-Step Digitalization Journey 437
18.1 Introduction 437
18.2 Digital Readiness Assessment 438
18.3 The Six-Step Digitalization Journey 449
18.4 Recommendations: A Digital Transformation Management System 454
18.5 Establishing a Digital Transformation Management System 455
References 457
19 Digital Project Evaluation and Development 459
19.1 Introduction 459
19.2 Business Case Evaluation 459
19.3 Digital Project Development Steps 461
19.4 Remarks on Digital Project Development 465
19.5 S-Curve for Project Review and Management 469
19.6 Basics of Economic Analysis 472
Reference 475
20 Application Case Studies 477
20.1 Introduction 477
20.2 Application Cases from Digital Twins 477
20.3 Applications from Other Digital Projects 481
References 506
Index 507
