Sustainable Manufacturing Systems: An Energy Perspective

Learn more about energy efficiency in traditional and advanced manufacturing settings with this leading and authoritative resource

Sustainable Manufacturing Systems: An Energy Perspective delivers a comprehensive analysis of energy efficiency in sustainable manufacturing. The book presents manufacturing modeling methods and energy efficiency evaluation and improvement methods for different manufacturing systems. It allows industry professionals to understand the methodologies and techniques being embraced around the world that lead to advanced energy management.

The book offers readers a comprehensive and systematic theoretical foundation for novel manufacturing system modeling, analysis, and control. It concludes with a summary of the insights and applications contained within and a discussion of future research issues that have yet to be grappled with.

Sustainable Manufacturing Systems answers the questions that energy customers, managers, decision makers, and researchers have been asking about sustainable manufacturing. The book’s release coincides with recent and profound advances in smart grid applications and will serve as a practical tool to assist industrial engineers in furthering the green revolution. Readers will also benefit from:

• A thorough introduction to energy efficiency in manufacturing systems, including the current state of research and research methodologies
• An exploration of the development of manufacturing methodologies, including mathematical modeling for manufacturing systems and energy efficiency characterization in manufacturing systems
• An analysis of the applications of various methodologies, including electricity demand response for manufacturing systems and energy control and optimization for manufacturing systems utilizing combined heat and power systems
• A discussion of energy efficiency in advanced manufacturing systems, like stereolithography additive manufacturing and cellulosic biofuel manufacturing systems

Perfect for researchers, undergraduate students, and graduate students in engineering disciplines, especially for those majoring in industrial, mechanical, electrical, and environmental engineering, Sustainable Manufacturing Systems will also earn a place in the libraries of management and business students interested in manufacturing system cost performance and energy management.

Lin Li, PhD, is an Assistant Professor in the Department of Mechanical and Industrial Engineering at the University of Illinois at Chicago. Dr. Li has published over sixty scientific papers in scholarly journals and 34 for conferences.

Mengchu Zhou, PhD, is a Distinguished Professor of Electrical and Computer Engineering at the New Jersey Institute of Technology (NJIT), in the United States. He is an Associate Editor of IEEE Transactions on Systems, Man, and Cybernetics Systems, and is a Fellow of the IEEE, IFAC, and AAAS.

Author Biography xv

Preface xvii

Acknowledgments xxiii

List of Figures xxv

Part I Introductions to Energy Efficiency in Manufacturing Systems 1

1 Introduction 3

1.1 Definitions and Practices of Sustainable Manufacturing 3

1.1.1 Current Status of Manufacturing Industry 3

1.1.2 Sustainability in the Manufacturing Sector and Associated Impacts 5

1.1.3 Sustainable Manufacturing Practices 10

1.2 Fundamental of Manufacturing Systems 12

1.2.1 Stages of Product Manufacturing 12

1.2.2 Classification of Manufacturing Systems 13

1.2.2.1 Job Shop 13

1.2.2.2 Project Shop 14

1.2.2.3 Cellular System 15

1.2.2.4 Flow Line 15

1.2.2.5 Continuous System 15

1.3 Problem Statement and Scope 18

Problems 19

References 19

2 Energy Efficiency in Manufacturing Systems 23

2.1 Energy Consumption in Manufacturing Systems 23

2.1.1 Energy and Power Basics 23

2.1.2 Energy Generation 24

2.1.2.1 Primary Energy 25

2.1.2.2 Secondary Energy 27

2.1.3 Energy Distribution 27

2.1.3.1 Electricity 28

2.1.3.2 Steam 30

2.1.3.3 Compressed Air 30

2.1.4 Energy Consumption 31

2.1.4.1 Indirect End Use 33

2.1.4.2 Direct Process End Use 33

2.1.4.3 Direct Non-process End Use 34

2.2 Energy Saving Potentials and Energy Management Strategies for Manufacturing Systems 35

2.2.1 Machine Level 39

2.2.1.1 Intrinsic Characteristics of Machine Tools 41

2.2.1.2 Processing Conditions 42

2.2.2 System Level 43

2.2.2.1 Inhomogeneous System 44

2.2.2.2 Machine Maintenance 45

2.2.3 Plant Level 46

2.2.3.1 Indirect End Use 46

2.2.3.2 Direct Non-process End Use 47

2.3 Demand-side Energy Management 49

2.3.1 Electricity Bill Components 50

2.3.1.1 Electricity Cost 51

2.3.1.2 Demand Cost 51

2.3.1.3 Fixed Cost 52

2.3.2 Energy Efficiency Programs 52

2.3.3 Demand Response Programs 55

2.3.3.1 Incentive-based Programs 56

2.3.3.2 Price Base Options 57

Problems 59

References 59

Part II Mathematical Tools and Modeling Basics 65

3 Mathematical Tools 67

3.1 Probability 67

3.1.1 Fundamentals of Probability Theory 67

3.1.1.1 Basics of Probability Theory 67

3.1.1.2 Axioms of Probability Theory 69

3.1.1.3 Conditional Probability and Independence 72

3.1.1.4 Total Probability Theorem 73

3.1.1.5 Bayes’ Law 74

3.1.2 Random Variables 74

3.1.2.1 Discrete Random Variables 75

3.1.2.2 Continuous Random Variables 82

3.1.3 Random Process 88

3.1.3.1 Discrete-time Markov Chain 89

3.1.3.2 Continuous-time Markov Chain 92

3.2 Petri Net 94

3.2.1 Formal Definition of Petri Net 95

3.2.1.1 Definition of Petri Net 95

3.2.2 Classical Petri Net 99

3.2.2.1 State Machine Petri Net 101

3.2.2.2 Marked Graph 102

3.2.2.3 Systematic Modeling Methods 105

3.2.3 Deterministic Timed Petri Net 106

3.2.4 Stochastic Petri Net 109

3.3 Optimization Methods 113

3.3.1 Fundamentals of Optimization 113

3.3.1.1 Objective Function 114

3.3.1.2 Decision Variables 114

3.3.1.3 Constraints 115

3.3.1.4 Local and Global Optimum 116

3.3.1.5 Near-optimal Solutions 117

3.3.1.6 Single-objective and Multi-objective Optimization 117

3.3.1.7 Deterministic and Stochastic Optimization 118

3.3.2 Genetic Algorithms 119

3.3.2.1 Initialization 119

3.3.2.2 Evaluation 121

3.3.2.3 Selection 121

3.3.2.4 Crossover 123

3.3.2.5 Mutation 124

3.3.2.6 Termination Criteria 125

3.3.3 Particle Swarm Optimizer (PSO) 126

3.3.3.1 Initialization 126

3.3.3.2 Evaluation 128

3.3.3.3 Personal and Global Best Positions 128

3.3.3.4 Updating Velocity and Position 129

3.3.3.5 Termination Criteria 132

Problems 132

References 134

4 Mathematical Modeling of Manufacturing Systems 139

4.1 Basics in Manufacturing System Modeling 139

4.1.1 Structure of Manufacturing Systems 139

4.1.1.1 Basic Components 139

4.1.1.2 Structural Modeling 140

4.1.1.3 Types of Manufacturing Systems 141

4.1.2 Mathematical Models of Machines and Buffers 142

4.1.2.1 Timing Issues for Machines 143

4.1.2.2 Machine Reliability Models 143

4.1.2.3 Parameters of Aggregated Machines 145

4.1.2.4 Mathematical Model of Buffers 146

4.1.2.5 Interaction Between Machines and Buffers 147

4.1.2.6 Buffer State Transition 147

4.1.2.7 Blockage and Starvation 148

4.1.3 Performance Measures 150

4.1.3.1 Blockage and Starvation 150

4.1.3.2 Production Rate and Throughput 151

4.1.3.3 Work-in-process 151

4.2 Two-machine Production Lines 152

4.2.1 Conventions and Notations 152

4.2.1.1 Assumptions 152

4.2.1.2 Notations 152

4.2.2 State Transition 154

4.2.2.1 State Transition Probabilities 155

4.2.2.2 System Dynamics 157

4.2.3 Steady-state Probabilities 157

4.2.3.1 Identical Machines 159

4.2.3.2 Nonidentical Machines 160

4.2.4 Performance Measures 161

4.2.4.1 Blockage and Starvation 161

4.2.4.2 Production Rate 161

4.2.4.3 Work-in-process 162

4.3 Multi-machine Production Lines 162

4.3.1 Assumptions and Notations 163

4.3.1.1 Assumptions 163

4.3.1.2 Notations 163

4.3.2 State Transition 164

4.3.2.1 State Transition Probabilities 165

4.3.2.2 System Dynamics 167

4.3.3 Performance Measures 167

4.3.3.1 Blockage and Starvation 167

4.3.3.2 Production Rate 168

4.3.3.3 Work-in-process 169

4.3.4 System Modeling with Iteration-based Method 169

4.4 Production Lines Coupled with Material Handling Systems 174

4.4.1 Assumptions and Notations 174

4.4.1.1 Assumptions 175

4.4.1.2 Notations 175

4.4.2 State Transition and Performance 175

4.4.2.1 Blockage and Starvation 175

4.4.2.2 Production Rate 176

Problems 179

References 180

5 Energy Efficiency Characterization in Manufacturing Systems 181

5.1 Energy Consumption Modeling 181

5.1.1 Operation-based Energy Modeling 182

5.1.2 Component-based Energy Modeling 185

5.1.3 System-level Energy Modeling 188

5.2 Energy Cost modeling 191

5.2.1 Energy Cost Under Flat Rate 192

5.2.1.1 Energy Consumption Cost 192

5.2.1.2 Demand Cost 192

5.2.2 Energy Cost Under Time-of-use Rate 196

5.2.2.1 Energy Consumption Cost 196

5.2.2.2 Demand Cost 198

5.2.3 Energy Cost Under Critical Peak Price (CPP) 199

5.2.3.1 Energy Consumption Cost 199

5.2.3.2 Demand Cost 200

Problems 203

References 203

Part III Energy Management in Typical Manufacturing Systems 205

6 Electricity Demand Response for Manufacturing Systems 207

6.1 Time-of-use Pricing for Manufacturing Systems 208

6.1.1 Introduction to TOU 208

6.1.2 Survey of TOU Pricing in US Utilities 209

6.1.3 Comparison of Energy Cost Between Flat Rate and TOU Rates 210

6.2 TOU-Based Production Scheduling for Manufacturing Systems 216

6.2.1 Manufacturing Systems Modeling 216

6.2.2 Energy Consumption and Energy Cost Modeling 218

6.2.3 Production Scheduling for TOU-based Demand Response 219

6.2.3.1 Production Scheduling Problem Formulation 219

6.2.3.2 PSO Algorithm for Near-optimal Solutions 220

6.2.3.3 Case Study Setup 221

6.2.3.4 Optimal Production Schedules 222

6.3 Critical Peak Pricing for Manufacturing Systems 228

6.3.1 Introduction to Critical Peak Pricing (CPP) 228

6.3.2 Comparison of Energy Cost Between TOU and CPP Rates 229

Problems 234

Appendix 3.A Supplementary Information of Demand Response Tariffs 235

References 255

7 Energy Control and Optimization for Manufacturing Systems Utilizing Combined Heat and Power System 257

7.1 Introduction to Combined Heat and Power System 257

7.2 Problem Definition and Modeling 258

7.2.1 Objective Function 260

7.2.1.1 Electricity Cost 260

7.2.1.2 Operation Cost for the CHP System and Boiler 261

7.2.2 Constraints 262

7.3 Solution Approach 263

7.3.1 Initialization 263

7.3.2 Evaluation 264

7.3.3 Updating Process 265

7.4 Case Study 266

7.4.1 Case Study Settings 267

7.4.2 Results and Discussions 269

Problems 270

References 271

8 Plant-level Energy Management for Combined Manufacturing and HVAC System 273

8.1 Definition and Modeling 273

8.1.1 Objective Function 274

8.1.1.1 Calculate TEL(t) 276

8.1.1.2 Estimate q(t) 278

8.1.2 Constraints 279

8.2 Solution Approach 281

8.2.1 Initialization 281

8.2.2 Evaluation 282

8.2.3 Updating Process 282

8.3 Case Study 283

8.3.1 Model Settings 284

8.3.2 Results and Discussions 287

Problems 289

References 290

Part IV Energy Management in Advanced Manufacturing Systems 291

9 Energy Analysis of Stereolithography-based Additive Manufacturing 293

9.1 Introduction to Additive Manufacturing 293

9.1.1 Illustration of MIP SL-based AM Process 294

9.2 Energy Consumption Modeling 296

9.2.1 Energy Consumption of UV Curing Process 297

9.2.2 Energy Consumption of Building Platform Movement 298

9.2.3 Energy Consumption of Cooling System 298

9.3 Experimentation 298

9.3.1 Experiment Design Methodology 298

9.3.2 Experiment Apparatus 299

9.4 Results and Discussions 300

9.4.1 Baseline Case Results Using Default Conditions 300

9.4.2 Factorial Analysis Results 302

9.4.3 Product Quality Comparison 305

Problems 308

References 308

10 Energy Efficiency Modeling and Optimization of Cellulosic Biofuel Manufacturing System 311

10.1 Introduction to Cellulosic Biofuel Manufacturing 311

10.2 Energy Modeling of Cellulosic Biofuel Production 313

10.2.1 Energy Modeling of Biomass Size Reduction Process 314

10.2.2 Energy Modeling of Biofuel Chemical Conversion Processes 314

10.2.2.1 Heating Energy 315

10.2.2.2 Energy Loss 316

10.2.2.3 Reaction Energy 317

10.2.2.4 Energy Recovery 320

10.2.2.5 Total Energy Consumption 321

10.3 Energy Consumption Optimization Using PSO 321

10.3.1 Problem Formulation 321

10.3.2 Solution Procedures 322

10.3.2.1 Initialization 322

10.3.2.2 Evaluation 323

10.3.2.3 Updating Process 323

10.4 Case Study 323

10.4.1 Case Settings 324

10.4.2 Energy Analysis of Baseline Case 324

10.4.2.1 Energy Consumption Breakdown 324

10.4.3 Energy Analysis of Optimal Results 327

Problems 328

References 329

11 Energy-consumption Minimized Scheduling of Flexible Manufacturing Systems 333

11.1 Introduction 334

11.2 Construction of Place-timed PN for FMS Scheduling 335

11.2.1 Basic Definitions of PN 335

11.2.2 Place-timed PN Scheduling Models of FMS 336

11.3 Energy Consumption Functions 338

11.3.1 Calculating the Earliest Firing Time of Transitions 339

11.3.2 Two Energy Consumption Functions 340

11.3.2.1 Energy Consumption Function E1 341

11.3.2.2 Energy Consumption Function E2 341

11.4 Dynamic Programming for Scheduling FMS 344

11.4.1 Formulation of DP for FMSs 344

11.4.1.1 States and Stages 344

11.4.1.2 State Transition Equation 344

11.4.1.3 Bellman Equation 345

11.4.2 Reachability Graph of PNS 345

11.4.3 DP Implementation for Scheduling FMS 347

11.5 Modified Dynamic Programming for Scheduling FMS 348

11.5.1 Evaluation Function of Transition Sequences 349

11.5.2 Heuristic Function 350

11.5.3 MDP Algorithm for FMS Scheduling 351

11.6 Case Study 353

11.7 Summary 358

Problems 358

References 359

Part V Summaries and Conclusions 363

12 Research Trends and Future Directions in Sustainable Industrial Development 365

12.1 Insights into Sustainable Industrial Development 365

12.2 Energy and Resource Efficiency in Manufacturing 366

12.2.1 Equipment Design 366

12.2.2 Smart Manufacturing 367

12.3 Industrial Symbiosis 369

12.4 Supply Chain Management 371

12.5 Circular Economy 373

12.6 Life Cycle Assessment 376

References 378

Glossary 387

Acronyms 391

Index 393

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