Sustainable Manufacturing Systems: An Energy Perspective

Cover
Title Page
Copyright Page
Contents
Author Biography
Preface
Acknowledgments
List of Figures
Part I Introductions to Energy Efficiency in Manufacturing Systems
Chapter 1 Introduction
1.1 Definitions and Practices of Sustainable Manufacturing
1.1.1 Current Status of Manufacturing Industry
1.1.2 Sustainability in the Manufacturing Sector and Associated Impacts
1.1.3 Sustainable Manufacturing Practices
1.2 Fundamental of Manufacturing Systems
1.2.1 Stages of Product Manufacturing
1.2.2 Classification of Manufacturing Systems
1.2.2.1 Job Shop
1.2.2.2 Project Shop
1.2.2.3 Cellular System
1.2.2.4 Flow Line
1.2.2.5 Continuous System
1.3 Problem Statement and Scope
Problems
References
Chapter 2 Energy Efficiency in Manufacturing Systems
2.1 Energy Consumption in Manufacturing Systems
2.1.1 Energy and Power Basics
2.1.2 Energy Generation
2.1.2.1 Primary Energy
2.1.2.2 Secondary Energy
2.1.3 Energy Distribution
2.1.3.1 Electricity
2.1.3.2 Steam
2.1.3.3 Compressed Air
2.1.4 Energy Consumption
2.1.4.1 Indirect End Use
2.1.4.2 Direct Process End Use
2.1.4.3 Direct Non-process End Use
2.2 Energy Saving Potentials and Energy Management Strategies for Manufacturing Systems
2.2.1 Machine Level
2.2.1.1 Intrinsic Characteristics of Machine Tools
2.2.1.2 Processing Conditions
2.2.2 System Level
2.2.2.1 Inhomogeneous System
2.2.2.2 Machine Maintenance
2.2.3 Plant Level
2.2.3.1 Indirect End Use
2.2.3.2 Direct Non-process End Use
2.3 Demand-side Energy Management
2.3.1 Electricity Bill Components
2.3.1.1 Electricity Cost
2.3.1.2 Demand Cost
2.3.1.3 Fixed Cost
2.3.2 Energy Efficiency Programs
2.3.3 Demand Response Programs
2.3.3.1 Incentive-based Programs
2.3.3.2 Price Base Options
Problems
References
Part II Mathematical Tools and Modeling Basics
Chapter 3 Mathematical Tools
3.1 Probability
3.1.1 Fundamentals of Probability Theory
3.1.1.1 Basics of Probability Theory
3.1.1.2 Axioms of Probability Theory
3.1.1.3 Conditional Probability and Independence
3.1.1.4 Total Probability Theorem
3.1.1.5 Bayes´ Law
3.1.2 Random Variables
3.1.2.1 Discrete Random Variables
3.1.2.2 Continuous Random Variables
3.1.3 Random Process
3.1.3.1 Discrete-time Markov Chain
3.1.3.2 Continuous-time Markov Chain
3.2 Petri Net
3.2.1 Formal Definition of Petri Net
3.2.1.1 Definition of Petri Net
Execution Rules of Petri Net
3.2.2 Classical Petri Net
3.2.2.1 State Machine Petri Net
3.2.2.2 Marked Graph
3.2.2.3 Systematic Modeling Methods
3.2.3 Deterministic Timed Petri Net
3.2.4 Stochastic Petri Net
3.3 Optimization Methods
3.3.1 Fundamentals of Optimization
3.3.1.1 Objective Function
3.3.1.2 Decision Variables
3.3.1.3 Constraints
3.3.1.4 Local and Global Optimum
3.3.1.5 Near-optimal Solutions
3.3.1.6 Single-objective and Multi-objective Optimization
3.3.1.7 Deterministic and Stochastic Optimization
3.3.2 Genetic Algorithms
3.3.2.1 Initialization
3.3.2.2 Evaluation
3.3.2.3 Selection
3.3.2.4 Crossover
3.3.2.5 Mutation
3.3.2.6 Termination Criteria
3.3.3 Particle Swarm Optimizer (PSO)
3.3.3.1 Initialization
3.3.3.2 Evaluation
3.3.3.3 Personal and Global Best Positions
3.3.3.4 Updating Velocity and Position
3.3.3.5 Termination Criteria
Problems
References
Chapter 4 Mathematical Modeling of Manufacturing Systems
4.1 Basics in Manufacturing System Modeling
4.1.1 Structure of Manufacturing Systems
4.1.1.1 Basic Components
4.1.1.2 Structural Modeling
4.1.1.3 Types of Manufacturing Systems
4.1.2 Mathematical Models of Machines and Buffers
4.1.2.1 Timing Issues for Machines
4.1.2.2 Machine Reliability Models
4.1.2.3 Parameters of Aggregated Machines
4.1.2.4 Mathematical Model of Buffers
4.1.2.5 Interaction Between Machines and Buffers
4.1.2.6 Buffer State Transition
4.1.2.7 Blockage and Starvation
4.1.3 Performance Measures
4.1.3.1 Blockage and Starvation
4.1.3.2 Production Rate and Throughput
4.1.3.3 Work-in-process
4.2 Two-machine Production Lines
4.2.1 Conventions and Notations
4.2.1.1 Assumptions
4.2.1.2 Notations
4.2.2 State Transition
4.2.2.1 State Transition Probabilities
4.2.2.2 System Dynamics
4.2.3 Steady-state Probabilities
4.2.3.1 Identical Machines
4.2.3.2 Nonidentical Machines
4.2.4 Performance Measures
4.2.4.1 Blockage and Starvation
4.2.4.2 Production Rate
4.2.4.3 Work-in-process
4.3 Multi-machine Production Lines
4.3.1 Assumptions and Notations
4.3.1.1 Assumptions
4.3.1.2 Notations
4.3.2 State Transition
4.3.2.1 State Transition Probabilities
4.3.2.2 System Dynamics
4.3.3 Performance Measures
4.3.3.1 Blockage and Starvation
4.3.3.2 Production Rate
4.3.3.3 Work-in-process
4.3.4 System Modeling with Iteration-based Method
4.4 Production Lines Coupled with Material Handling Systems
4.4.1 Assumptions and Notations
4.4.1.1 Assumptions
4.4.1.2 Notations
4.4.2 State Transition and Performance
4.4.2.1 Blockage and Starvation
4.4.2.2 Production Rate
Problems
References
Chapter 5 Energy Efficiency Characterization in Manufacturing Systems
5.1 Energy Consumption Modeling
5.1.1 Operation-based Energy Modeling
5.1.2 Component-based Energy Modeling
5.1.3 System-level Energy Modeling
5.2 Energy Cost Modeling
5.2.1 Energy Cost Under Flat Rate
5.2.1.1 Energy Consumption Cost
5.2.1.2 Demand Cost
5.2.2 Energy Cost Under Time-of-use Rate
5.2.2.1 Energy Consumption Cost
5.2.2.2 Demand Cost
5.2.3 Energy Cost Under Critical Peak Price (CPP)
5.2.3.1 Energy Consumption Cost
5.2.3.2 Demand Cost
Problems
References
Part III Energy Management in Typical Manufacturing Systems
Chapter 6 Electricity Demand Response for Manufacturing Systems
6.1 Time-of-use Pricing for Manufacturing Systems
6.1.1 Introduction to TOU
6.1.2 Survey of TOU Pricing in US Utilities
6.1.3 Comparison of Energy Cost Between Flat Rate and TOU Rates
6.2 TOU-based Production Scheduling for Manufacturing Systems
6.2.1 Manufacturing Systems Modeling
6.2.2 Energy Consumption and Energy Cost Modeling
6.2.3 Production Scheduling for TOU-based Demand Response
6.2.3.1 Production Scheduling Problem Formulation
6.2.3.2 PSO Algorithm for Near-optimal Solutions
6.2.3.3 Case Study Setup
6.2.3.4 Optimal Production Schedules
6.3 Critical Peak Pricing for Manufacturing Systems
6.3.1 Introduction to Critical Peak Pricing (CPP)
6.3.2 Comparison of Energy Cost Between TOU and CPP Rates
Problems
Appendix 3.A Supplementary Information of Demand Response Tariffs
References
Chapter 7 Energy Control and Optimization for Manufacturing Systems Utilizing Combined Heat and Power System
7.1 Introduction to Combined Heat and Power System
7.2 Problem Definition and Modeling
7.2.1 Objective Function
7.2.1.1 Electricity Cost
7.2.1.2 Operation Cost for the CHP System and Boiler
7.2.2 Constraints
7.3 Solution Approach
7.3.1 Initialization
7.3.2 Evaluation
7.3.3 Updating Process
7.4 Case Study
7.4.1 Case Study Settings
7.4.2 Results and Discussions
Problems
References
Chapter 8 Plant-level Energy Management for Combined Manufacturing and HVAC System
8.1 Definition and Modeling
8.1.1 Objective Function
8.1.1.1 Calculate TEL(t)
8.1.1.2 Estimate q(t)
8.1.2 Constraints
8.2 Solution Approach
8.2.1 Initialization
8.2.2 Evaluation
8.2.3 Updating Process
8.3 Case Study
8.3.1 Model Settings
8.3.2 Results and Discussions
Problems
References
Part IV Energy Management in Advanced Manufacturing Systems
Chapter 9 Energy Analysis of Stereolithography-based Additive Manufacturing
9.1 Introduction to Additive Manufacturing
9.1.1 Illustration of MIP SL-based AM Process
9.2 Energy Consumption Modeling
9.2.1 Energy Consumption of UV Curing Process
9.2.2 Energy Consumption of Building Platform Movement
9.2.3 Energy Consumption of Cooling System
9.3 Experimentation
9.3.1 Experiment Design Methodology
9.3.2 Experiment Apparatus
9.4 Results and Discussions
9.4.1 Baseline Case Results Using Default Conditions
9.4.2 Factorial Analysis Results
9.4.3 Product Quality Comparison
Problems
References
Chapter 10 Energy Efficiency Modeling and Optimization of Cellulosic Biofuel Manufacturing System
10.1 Introduction to Cellulosic Biofuel Manufacturing
10.2 Energy Modeling of Cellulosic Biofuel Production
10.2.1 Energy Modeling of Biomass Size Reduction Process
10.2.2 Energy Modeling of Biofuel Chemical Conversion Processes
10.2.2.1 Heating Energy
10.2.2.2 Energy Loss
10.2.2.3 Reaction Energy
10.2.2.4 Energy Recovery
10.2.2.5 Total Energy Consumption
10.3 Energy Consumption Optimization Using PSO
10.3.1 Problem Formulation
10.3.2 Solution Procedures
10.3.2.1 Initialization
10.3.2.2 Evaluation
10.3.2.3 Updating Process
10.4 Case Study
10.4.1 Case Settings
10.4.2 Energy Analysis of Baseline Case
10.4.2.1 Energy Consumption Breakdown
10.4.3 Energy Analysis of Optimal Results
Problems
References
Chapter 11 Energy-consumption Minimized Scheduling of Flexible Manufacturing Systems
11.1 Introduction
11.2 Construction of Place-timed PN for FMS Scheduling
11.2.1 Basic Definitions of PN
11.2.2 Place-timed PN Scheduling Models of FMS
11.3 Energy Consumption Functions
11.3.1 Calculating the Earliest Firing Time of Transitions
11.3.2 Two Energy Consumption Functions
11.3.2.1 Energy Consumption Function E1
11.3.2.2 Energy Consumption Function E2
11.4 Dynamic Programming for Scheduling FMS
11.4.1 Formulation of DP for FMSs
11.4.1.1 States and Stages
11.4.1.2 State Transition Equation
11.4.1.3 Bellman Equation
11.4.2 Reachability Graph of PNS
11.4.3 DP Implementation for Scheduling FMS
11.5 Modified Dynamic Programming for Scheduling FMS
11.5.1 Evaluation Function of Transition Sequences
11.5.2 Heuristic Function
11.5.3 MDP Algorithm for FMS Scheduling
11.6 Case Study
11.7 Summary
Problems
References
Part V Summaries and Conclusions
Chapter 12 Research Trends and Future Directions in Sustainable Industrial Development
12.1 Insights into Sustainable Industrial Development
12.2 Energy and Resource Efficiency in Manufacturing
12.2.1 Equipment Design
12.2.2 Smart Manufacturing
12.3 Industrial Symbiosis
12.4 Supply Chain Management
12.5 Circular Economy
12.6 Life Cycle Assessment
References
Glossary
Acronyms
Index
EULA