Sustainable Manufacturing Systems: An Energy Perspective

ISBN-13: 9781119578246 / Angielski / Twarda / 2022 / 400 str.

Lin Li; Mengchu Zhou

Spis treści

Author Biography xvPreface xviiAcknowledgments xxiiiList of Figures xxvPart I Introductions to Energy Efficiency in Manufacturing Systems 11 Introduction 31.1 Definitions and Practices of Sustainable Manufacturing 31.1.1 Current Status of Manufacturing Industry 31.1.2 Sustainability in the Manufacturing Sector and Associated Impacts 51.1.3 Sustainable Manufacturing Practices 101.2 Fundamental of Manufacturing Systems 121.2.1 Stages of Product Manufacturing 121.2.2 Classification of Manufacturing Systems 131.2.2.1 Job Shop 131.2.2.2 Project Shop 141.2.2.3 Cellular System 151.2.2.4 Flow Line 151.2.2.5 Continuous System 151.3 Problem Statement and Scope 18Problems 19References 192 Energy Efficiency in Manufacturing Systems 232.1 Energy Consumption in Manufacturing Systems 232.1.1 Energy and Power Basics 232.1.2 Energy Generation 242.1.2.1 Primary Energy 252.1.2.2 Secondary Energy 272.1.3 Energy Distribution 272.1.3.1 Electricity 282.1.3.2 Steam 302.1.3.3 Compressed Air 302.1.4 Energy Consumption 312.1.4.1 Indirect End Use 332.1.4.2 Direct Process End Use 332.1.4.3 Direct Non-process End Use 342.2 Energy Saving Potentials and Energy Management Strategies for Manufacturing Systems 352.2.1 Machine Level 392.2.1.1 Intrinsic Characteristics of Machine Tools 412.2.1.2 Processing Conditions 422.2.2 System Level 432.2.2.1 Inhomogeneous System 442.2.2.2 Machine Maintenance 452.2.3 Plant Level 462.2.3.1 Indirect End Use 462.2.3.2 Direct Non-process End Use 472.3 Demand-side Energy Management 492.3.1 Electricity Bill Components 502.3.1.1 Electricity Cost 512.3.1.2 Demand Cost 512.3.1.3 Fixed Cost 522.3.2 Energy Efficiency Programs 522.3.3 Demand Response Programs 552.3.3.1 Incentive-based Programs 562.3.3.2 Price Base Options 57Problems 59References 59Part II Mathematical Tools and Modeling Basics 653 Mathematical Tools 673.1 Probability 673.1.1 Fundamentals of Probability Theory 673.1.1.1 Basics of Probability Theory 673.1.1.2 Axioms of Probability Theory 693.1.1.3 Conditional Probability and Independence 723.1.1.4 Total Probability Theorem 733.1.1.5 Bayes' Law 743.1.2 Random Variables 743.1.2.1 Discrete Random Variables 753.1.2.2 Continuous Random Variables 823.1.3 Random Process 883.1.3.1 Discrete-time Markov Chain 893.1.3.2 Continuous-time Markov Chain 923.2 Petri Net 943.2.1 Formal Definition of Petri Net 953.2.1.1 Definition of Petri Net 953.2.2 Classical Petri Net 993.2.2.1 State Machine Petri Net 1013.2.2.2 Marked Graph 1023.2.2.3 Systematic Modeling Methods 1053.2.3 Deterministic Timed Petri Net 1063.2.4 Stochastic Petri Net 1093.3 Optimization Methods 1133.3.1 Fundamentals of Optimization 1133.3.1.1 Objective Function 1143.3.1.2 Decision Variables 1143.3.1.3 Constraints 1153.3.1.4 Local and Global Optimum 1163.3.1.5 Near-optimal Solutions 1173.3.1.6 Single-objective and Multi-objective Optimization 1173.3.1.7 Deterministic and Stochastic Optimization 1183.3.2 Genetic Algorithms 1193.3.2.1 Initialization 1193.3.2.2 Evaluation 1213.3.2.3 Selection 1213.3.2.4 Crossover 1233.3.2.5 Mutation 1243.3.2.6 Termination Criteria 1253.3.3 Particle Swarm Optimizer (PSO) 1263.3.3.1 Initialization 1263.3.3.2 Evaluation 1283.3.3.3 Personal and Global Best Positions 1283.3.3.4 Updating Velocity and Position 1293.3.3.5 Termination Criteria 132Problems 132References 1344 Mathematical Modeling of Manufacturing Systems 1394.1 Basics in Manufacturing System Modeling 1394.1.1 Structure of Manufacturing Systems 1394.1.1.1 Basic Components 1394.1.1.2 Structural Modeling 1404.1.1.3 Types of Manufacturing Systems 1414.1.2 Mathematical Models of Machines and Buffers 1424.1.2.1 Timing Issues for Machines 1434.1.2.2 Machine Reliability Models 1434.1.2.3 Parameters of Aggregated Machines 1454.1.2.4 Mathematical Model of Buffers 1464.1.2.5 Interaction Between Machines and Buffers 1474.1.2.6 Buffer State Transition 1474.1.2.7 Blockage and Starvation 1484.1.3 Performance Measures 1504.1.3.1 Blockage and Starvation 1504.1.3.2 Production Rate and Throughput 1514.1.3.3 Work-in-process 1514.2 Two-machine Production Lines 1524.2.1 Conventions and Notations 1524.2.1.1 Assumptions 1524.2.1.2 Notations 1524.2.2 State Transition 1544.2.2.1 State Transition Probabilities 1554.2.2.2 System Dynamics 1574.2.3 Steady-state Probabilities 1574.2.3.1 Identical Machines 1594.2.3.2 Nonidentical Machines 1604.2.4 Performance Measures 1614.2.4.1 Blockage and Starvation 1614.2.4.2 Production Rate 1614.2.4.3 Work-in-process 1624.3 Multi-machine Production Lines 1624.3.1 Assumptions and Notations 1634.3.1.1 Assumptions 1634.3.1.2 Notations 1634.3.2 State Transition 1644.3.2.1 State Transition Probabilities 1654.3.2.2 System Dynamics 1674.3.3 Performance Measures 1674.3.3.1 Blockage and Starvation 1674.3.3.2 Production Rate 1684.3.3.3 Work-in-process 1694.3.4 System Modeling with Iteration-based Method 1694.4 Production Lines Coupled with Material Handling Systems 1744.4.1 Assumptions and Notations 1744.4.1.1 Assumptions 1754.4.1.2 Notations 1754.4.2 State Transition and Performance 1754.4.2.1 Blockage and Starvation 1754.4.2.2 Production Rate 176Problems 179References 1805 Energy Efficiency Characterization in Manufacturing Systems 1815.1 Energy Consumption Modeling 1815.1.1 Operation-based Energy Modeling 1825.1.2 Component-based Energy Modeling 1855.1.3 System-level Energy Modeling 1885.2 Energy Cost modeling 1915.2.1 Energy Cost Under Flat Rate 1925.2.1.1 Energy Consumption Cost 1925.2.1.2 Demand Cost 1925.2.2 Energy Cost Under Time-of-use Rate 1965.2.2.1 Energy Consumption Cost 1965.2.2.2 Demand Cost 1985.2.3 Energy Cost Under Critical Peak Price (CPP) 1995.2.3.1 Energy Consumption Cost 1995.2.3.2 Demand Cost 200Problems 203References 203Part III Energy Management in Typical Manufacturing Systems 2056 Electricity Demand Response for Manufacturing Systems 2076.1 Time-of-use Pricing for Manufacturing Systems 2086.1.1 Introduction to TOU 2086.1.2 Survey of TOU Pricing in US Utilities 2096.1.3 Comparison of Energy Cost Between Flat Rate and TOU Rates 2106.2 TOU-Based Production Scheduling for Manufacturing Systems 2166.2.1 Manufacturing Systems Modeling 2166.2.2 Energy Consumption and Energy Cost Modeling 2186.2.3 Production Scheduling for TOU-based Demand Response 2196.2.3.1 Production Scheduling Problem Formulation 2196.2.3.2 PSO Algorithm for Near-optimal Solutions 2206.2.3.3 Case Study Setup 2216.2.3.4 Optimal Production Schedules 2226.3 Critical Peak Pricing for Manufacturing Systems 2286.3.1 Introduction to Critical Peak Pricing (CPP) 2286.3.2 Comparison of Energy Cost Between TOU and CPP Rates 229Problems 234Appendix 3.A Supplementary Information of Demand Response Tariffs 235References 2557 Energy Control and Optimization for Manufacturing Systems Utilizing Combined Heat and Power System 2577.1 Introduction to Combined Heat and Power System 2577.2 Problem Definition and Modeling 2587.2.1 Objective Function 2607.2.1.1 Electricity Cost 2607.2.1.2 Operation Cost for the CHP System and Boiler 2617.2.2 Constraints 2627.3 Solution Approach 2637.3.1 Initialization 2637.3.2 Evaluation 2647.3.3 Updating Process 2657.4 Case Study 2667.4.1 Case Study Settings 2677.4.2 Results and Discussions 269Problems 270References 2718 Plant-level Energy Management for Combined Manufacturing and HVAC System 2738.1 Definition and Modeling 2738.1.1 Objective Function 2748.1.1.1 Calculate TEL(t) 2768.1.1.2 Estimate q(t) 2788.1.2 Constraints 2798.2 Solution Approach 2818.2.1 Initialization 2818.2.2 Evaluation 2828.2.3 Updating Process 2828.3 Case Study 2838.3.1 Model Settings 2848.3.2 Results and Discussions 287Problems 289References 290Part IV Energy Management in Advanced Manufacturing Systems 2919 Energy Analysis of Stereolithography-based Additive Manufacturing 2939.1 Introduction to Additive Manufacturing 2939.1.1 Illustration of MIP SL-based AM Process 2949.2 Energy Consumption Modeling 2969.2.1 Energy Consumption of UV Curing Process 2979.2.2 Energy Consumption of Building Platform Movement 2989.2.3 Energy Consumption of Cooling System 2989.3 Experimentation 2989.3.1 Experiment Design Methodology 2989.3.2 Experiment Apparatus 2999.4 Results and Discussions 3009.4.1 Baseline Case Results Using Default Conditions 3009.4.2 Factorial Analysis Results 3029.4.3 Product Quality Comparison 305Problems 308References 30810 Energy Efficiency Modeling and Optimization of Cellulosic Biofuel Manufacturing System 31110.1 Introduction to Cellulosic Biofuel Manufacturing 31110.2 Energy Modeling of Cellulosic Biofuel Production 31310.2.1 Energy Modeling of Biomass Size Reduction Process 31410.2.2 Energy Modeling of Biofuel Chemical Conversion Processes 31410.2.2.1 Heating Energy 31510.2.2.2 Energy Loss 31610.2.2.3 Reaction Energy 31710.2.2.4 Energy Recovery 32010.2.2.5 Total Energy Consumption 32110.3 Energy Consumption Optimization Using PSO 32110.3.1 Problem Formulation 32110.3.2 Solution Procedures 32210.3.2.1 Initialization 32210.3.2.2 Evaluation 32310.3.2.3 Updating Process 32310.4 Case Study 32310.4.1 Case Settings 32410.4.2 Energy Analysis of Baseline Case 32410.4.2.1 Energy Consumption Breakdown 32410.4.3 Energy Analysis of Optimal Results 327Problems 328References 32911 Energy-consumption Minimized Scheduling of Flexible Manufacturing Systems 33311.1 Introduction 33411.2 Construction of Place-timed PN for FMS Scheduling 33511.2.1 Basic Definitions of PN 33511.2.2 Place-timed PN Scheduling Models of FMS 33611.3 Energy Consumption Functions 33811.3.1 Calculating the Earliest Firing Time of Transitions 33911.3.2 Two Energy Consumption Functions 34011.3.2.1 Energy Consumption Function E1 34111.3.2.2 Energy Consumption Function E2 34111.4 Dynamic Programming for Scheduling FMS 34411.4.1 Formulation of DP for FMSs 34411.4.1.1 States and Stages 34411.4.1.2 State Transition Equation 34411.4.1.3 Bellman Equation 34511.4.2 Reachability Graph of PNS 34511.4.3 DP Implementation for Scheduling FMS 34711.5 Modified Dynamic Programming for Scheduling FMS 34811.5.1 Evaluation Function of Transition Sequences 34911.5.2 Heuristic Function 35011.5.3 MDP Algorithm for FMS Scheduling 35111.6 Case Study 35311.7 Summary 358Problems 358References 359Part V Summaries and Conclusions 36312 Research Trends and Future Directions in Sustainable Industrial Development 36512.1 Insights into Sustainable Industrial Development 36512.2 Energy and Resource Efficiency in Manufacturing 36612.2.1 Equipment Design 36612.2.2 Smart Manufacturing 36712.3 Industrial Symbiosis 36912.4 Supply Chain Management 37112.5 Circular Economy 37312.6 Life Cycle Assessment 376References 378Glossary 387Acronyms 391Index 393

O autorze

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.