Sustainable Manufacturing Systems

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