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Foreword |
7 |
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Cyber-Physical Systems for Production Technology |
7 |
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Contents |
11 |
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About the Editors |
15 |
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Introduction and Overview |
18 |
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1 Industrial Internet of Things and Cyber Manufacturing Systems |
19 |
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1 Introduction |
19 |
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2 Foundations of the Industrial Internet of Things and Cyber Manufacturing Systems |
20 |
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3 Potentials and Challenges |
24 |
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4 Major Research Initiatives |
26 |
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5 Approaches and Solutions |
27 |
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5.1 Modeling for CPS and CMS |
27 |
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5.2 Architectural Design Patterns for CMS and IIoT |
29 |
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5.3 Communication and Networking |
30 |
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5.4 Artificial Intelligence and Analytics |
30 |
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5.5 Evolution of Workforce and Human-Machine-Interaction |
32 |
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6 A Glance into the Future: Towards Autonomous Networked Manufacturing Systems |
33 |
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Acknowledgments |
34 |
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References |
34 |
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2 An Application Map for Industrial Cyber-Physical Systems |
36 |
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1 An Introduction to Cyber-Physical Systems |
36 |
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2 Foundations of Industrial Cyber-Physical Systems |
37 |
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2.1 Technical Dimension of Cyber-Physical Systems |
38 |
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2.2 Human Dimension of Cyber-Physical Systems |
39 |
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2.3 Organizational Dimension of Cyber-Physical Systems |
40 |
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3 Categories of Potential Improvement for Industrial Cyber-Physical Systems |
42 |
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3.1 Automatization |
44 |
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3.2 Autonomization |
45 |
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3.3 Human-Machine Interaction |
46 |
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3.4 Decentralization |
47 |
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3.5 Digitization for Process Alignment |
47 |
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3.6 Big Data |
48 |
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3.7 Cyber Security |
49 |
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3.8 Knowledge Management |
49 |
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3.9 Qualification |
50 |
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4 Elaboration of an Application Map for Industrial Cyber-Physical Systems |
50 |
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4.1 Smart Factory |
51 |
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4.2 Industrial Smart Data |
52 |
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4.3 Industrial Smart Services |
54 |
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4.4 Smart Products |
55 |
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4.5 Product-Related Smart Data |
56 |
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4.6 Product-Related Smart Services |
57 |
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4.7 Utilization of the Application Map |
57 |
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5 Summary and Outlook |
59 |
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References |
60 |
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3 Cyber-Physical Electronics Production |
62 |
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1 Trends and Requirements in Modern Electronics Production |
62 |
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1.1 Miniaturization and Function Integration |
63 |
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1.2 Flexibility and Complexity |
65 |
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1.3 Logistics and Production Concepts |
67 |
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2 Enabling E-CPS Technologies |
71 |
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2.1 Sensor Integration, Printing Technologies and Communications |
71 |
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2.2 Software Systems |
74 |
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2.3 Autonomous and Smart One-Piece-Flow |
79 |
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3 Concept of a Cyber-Physical Electronics Production System |
83 |
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3.1 Self-Learning Electronics Production Processes |
84 |
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3.2 Assistance Systems |
86 |
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3.3 Integrated Cyber-Physical Electronics Production |
89 |
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References |
91 |
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Modeling for CPS and CMS |
94 |
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4 Cyber-Physical Systems Engineering for Manufacturing |
95 |
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1 Introduction |
95 |
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2 Cyber-Physical Systems |
96 |
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3 Systems Engineering |
97 |
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4 Manufacturing Innovation |
98 |
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5 Smart Manufacturing Systems Programs at NIST |
99 |
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5.1 Smart Manufacturing Systems Design and Analysis |
100 |
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5.1.1 Modeling Methodologies for Manufacturing System Analysis |
101 |
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5.1.2 Predictive Analytics for Manufacturing Systems |
102 |
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5.1.3 Performance Measurement for Smart Manufacturing |
104 |
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5.1.4 Service-Based Manufacturing and Service Composition |
105 |
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5.2 Smart Manufacturing Operations Planning and Control |
107 |
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5.2.1 Digital Thread for Smart Manufacturing |
108 |
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5.2.2 Systems Analysis Integration for Smart Manufacturing Operations |
112 |
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5.2.3 Wireless Systems for Industrial Environments |
112 |
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5.2.4 Cybersecurity for Smart Manufacturing Systems |
115 |
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5.2.5 Prognostics, Health Management and Control |
116 |
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5.2.6 Smart Manufacturing Systems Test Bed |
118 |
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6 Summary and Concluding Remarks |
119 |
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References |
120 |
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5 Model-Based Engineering of Supervisory Controllers for Cyber-Physical Systems |
125 |
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1 Introduction |
125 |
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1.1 Model-Based Systems Engineering |
125 |
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1.2 Structure of This Chapter |
128 |
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2 Synthesis-Based Development of Coordination Control |
128 |
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3 Description of an AGV System |
131 |
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3.1 Components of the Multi Mover |
132 |
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3.2 Interaction of the Components |
133 |
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4 Hybrid Models of the Uncontrolled System |
134 |
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4.1 Multi Mover High-Level Modes and Movement |
135 |
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4.2 Drive Motor |
136 |
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4.3 Steer Motor |
137 |
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4.4 Ride Control |
137 |
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4.5 Battery Sensor |
137 |
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4.6 Proximity Sensor |
138 |
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4.7 Bumper Switch |
138 |
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4.8 LEDs and Buttons |
139 |
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4.9 Abstraction Form Hybrid Automata to Discrete-Event Models |
139 |
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5 Requirements of the System |
140 |
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5.1 Emergency and Error Handling |
140 |
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5.2 LED Actuation |
141 |
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5.3 Motor Actuation |
141 |
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5.4 Button Handling |
143 |
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5.5 Proximity Sensors and Ride Control Handling |
144 |
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6 Synthesis of Supervisory Controller |
145 |
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7 Simulation-Based Visualization |
146 |
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8 Concluding Remarks |
148 |
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References |
148 |
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6 Formal Verification of SystemC-based Cyber Components |
151 |
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1 Introduction |
151 |
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2 Related Work |
153 |
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3 Preliminaries |
155 |
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3.1 Bounded Model Checking and Induction |
155 |
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3.2 SystemC Basics |
156 |
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4 TLM Property Checking |
156 |
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4.1 Simplified Model of the SystemC Kernel |
157 |
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4.2 Model Generation |
161 |
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4.2.1 SystemC to SCTLMD |
161 |
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4.2.2 Kernel Integration |
162 |
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4.2.3 Limitations |
163 |
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4.3 Property Language and Monitor Generation |
165 |
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4.3.1 Simple Safety Properties |
166 |
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4.3.2 Transaction Properties |
166 |
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4.3.3 System-Level Properties |
167 |
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4.4 BMC-Based Verification |
167 |
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5 Induction-Based TLM Property Checking |
169 |
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6 Experiments |
172 |
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6.1 BMC-Based Verification |
173 |
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6.1.1 FIFO Design |
173 |
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6.1.2 TLM-2.0 Design |
174 |
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6.2 Induction-Based Verification |
176 |
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6.2.1 FIFO Design and TLM-2.0 Design |
176 |
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6.2.2 JPEG Encoder |
177 |
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6.2.3 Chain Benchmark |
178 |
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6.3 Summary of Experimental Results |
179 |
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7 Conclusions |
179 |
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References |
179 |
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7 Evaluation Model for Assessment of Cyber-Physical Production Systems |
182 |
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1 Introduction |
182 |
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1.1 Motivation |
183 |
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2 A First Analysis of Value-Adds |
185 |
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3 State-of-the-Art |
187 |
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4 Approach and Methodology |
191 |
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5 Abilities of Cyber-Physical Systems |
193 |
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5.1 Abilities of Capturing and Processing Data and Information |
194 |
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5.2 Abilities of High-Quality Analysis with Artificial Intelligence |
195 |
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6 Advanced Abilities |
196 |
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6.1 The “Industrie 4.0” Component |
197 |
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6.2 Artificial Intelligence |
198 |
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7 Performance Indicators |
200 |
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7.1 Identified Performance Indicators |
201 |
|
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7.2 Performance Indicators of the Overall Systems Architecture |
202 |
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7.2.1 Modularity |
202 |
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7.2.2 Complexity |
203 |
|
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7.3 Performance Indicators of Production Operation |
203 |
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7.3.1 Maintainability |
203 |
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7.3.2 Production Efficiency |
204 |
|
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7.4 Performance Indicators of Changing Production Systems |
204 |
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7.4.1 Re-configurability |
204 |
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7.4.2 Automatic Planning |
204 |
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7.4.3 Automatic Adaptation |
205 |
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7.5 Performance Indicators of Cyber Support |
205 |
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7.5.1 Social Interaction |
205 |
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7.5.2 Support of Decisions |
205 |
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7.5.3 Further Characteristics: Usability |
206 |
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7.6 Relation Between Performance Indicators and Abilities |
206 |
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8 Validation |
206 |
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9 Conclusion |
208 |
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10 Further Work |
210 |
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References |
210 |
|
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Architectural Design Patterns for CMS and IIoT |
213 |
|
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8 CPS-Based Manufacturing with Semantic Object Memories and Service Orchestration for Industrie 4.0 Applications |
214 |
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1 Introduction |
214 |
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2 Use Cases |
216 |
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2.1 Use Case 1: Orchestrated Production |
219 |
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2.2 Use Case 2: Automated Maintenance |
220 |
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2.3 Use Case 3: Priority Management |
221 |
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3 Related Work |
222 |
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3.1 Semantic Technologies |
222 |
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3.2 Hardware Requirements |
223 |
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3.3 M2M Communication |
224 |
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3.4 Digital Object Representations |
225 |
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3.5 Conclusion |
227 |
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4 Digital Object Memories |
227 |
|
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4.1 Data Model |
228 |
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4.2 Storage Infrastructure |
230 |
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4.3 Communication Interfaces |
232 |
|
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5 Semantic Service Orchestration |
233 |
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5.1 Service Discovery |
234 |
|
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5.2 Semantic Orchestration |
235 |
|
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6 Conclusion |
237 |
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References |
238 |
|
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9 Integration of a Knowledge Database and Machine Vision Within a Robot-Based CPS |
241 |
|
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1 Introduction |
241 |
|
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2 Terms and Conditions |
242 |
|
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3 Research Efforts |
243 |
|
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4 Handling Dangerous Goods Using Industrial Machine Vision |
244 |
|
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4.1 Analysis of the Process Flow and the Boundary Conditions |
245 |
|
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4.2 Solution |
246 |
|
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4.3 Detection the Orientation of the Manhole Cover |
248 |
|
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4.4 Examination of Manhole Cover Seal |
249 |
|
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4.5 Operator Interface of the System |
249 |
|
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4.6 Control and Communication Concept |
250 |
|
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4.7 Conclusion |
251 |
|
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5 Laundry Logistics in Conjunction with RFID Systems |
251 |
|
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5.1 Prospective Applications of Industry 4.0 in the Textile Industry |
253 |
|
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5.2 Implementation of Industry 4.0 Within Industrial Laundries |
254 |
|
|
5.3 Conclusion |
256 |
|
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6 Production, in Particular Assembly with the Help of Physical Human-Robot Interaction (PHRI) |
257 |
|
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6.1 Challenges |
257 |
|
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6.1.1 Objectives and Approach |
257 |
|
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6.1.2 Description of Process |
258 |
|
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6.2 Planning |
259 |
|
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6.2.1 Analysis |
259 |
|
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6.2.2 Sub Problems |
259 |
|
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6.2.3 Requirements |
259 |
|
|
6.3 Applied Technologies |
260 |
|
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6.3.1 Robotics |
260 |
|
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6.3.2 Machine Vision and Data Bases |
260 |
|
|
6.3.3 Pre-separation |
260 |
|
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6.3.4 Robotics and Cell |
261 |
|
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6.3.5 Tools Used |
261 |
|
|
6.3.6 Human Machine Interface |
262 |
|
|
6.3.7 Search Strategy |
264 |
|
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6.3.8 Image Processing and Database |
264 |
|
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6.4 Procedure for Developing the Solution |
265 |
|
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6.5 Summary |
266 |
|
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7 Research Challenges and Conclusions |
267 |
|
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References |
268 |
|
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10 Interoperability in Smart Automation of Cyber Physical Systems |
271 |
|
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1 Introduction |
271 |
|
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2 Related Work |
273 |
|
|
2.1 Machine-Machine Interaction |
273 |
|
|
2.1.1 Field Bus Systems and the Industrial Ethernet |
274 |
|
|
2.1.2 Data Distribution Service (DDS) |
275 |
|
|
2.1.3 OPC Unified Architecture |
276 |
|
|
2.2 Human-Robot-Interaction |
279 |
|
|
3 Holistic Interoperability in Production Networks |
282 |
|
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3.1 Interoperability on Machine-Machine-Level Using OPC UA and Semantic Technologies |
282 |
|
|
3.2 Using Artificial Intelligence to Learn from Data |
283 |
|
|
4 Towards Interoperability in Human-Robot Interaction |
284 |
|
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4.1 System Design |
285 |
|
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4.2 Gathering |
285 |
|
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4.3 Recognition and Evaluation |
286 |
|
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4.4 Respond |
286 |
|
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5 Use Cases |
287 |
|
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5.1 Adaptable Demonstrator for Flexible Production Organization |
287 |
|
|
5.2 Virtual Production Intelligence Platform |
290 |
|
|
5.3 Canoe |
292 |
|
|
6 Conclusion |
293 |
|
|
References |
294 |
|
|
11 Enhancing Resiliency in Production Facilities Through Cyber Physical Systems |
297 |
|
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1 Introduction |
297 |
|
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2 The Need for Resilient Factories in the Context of Industry 4.0 |
298 |
|
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2.1 Cyber-Physical Systems, Self-Optimization and the Internet of Things |
298 |
|
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2.1.1 Cyber-Physical Systems (CPS) |
298 |
|
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2.1.2 Cyber-Physical Production System (CPPS) |
299 |
|
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2.1.3 Self-Optimization |
300 |
|
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2.1.4 Internet of Things |
300 |
|
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2.1.5 Industry 4.0 |
301 |
|
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2.2 Resilient Production Systems |
301 |
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2.2.1 Market Trend Customized Products |
301 |
|
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2.2.2 Technology Trend Cyber-Physical Production Systems |
302 |
|
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2.2.3 Global Trend of Energy and Resource Efficiency |
303 |
|
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2.2.4 The Resilient Factory as a Response to the Given Trends |
303 |
|
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3 Objectives of the Resilient Factory |
304 |
|
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4 Two Example Cases for Cyber-Physical Systems in Production |
306 |
|
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4.1 Energy-Oriented Manufacturing Planning and Control System |
306 |
|
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4.1.1 Requirements and Conditions |
306 |
|
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4.1.2 Concept and Procedure |
308 |
|
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4.1.3 Applications and Potentials |
311 |
|
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4.2 Smart Glasses in Industrial Assembly |
311 |
|
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4.2.1 Overview of Smart Devices Established on the Market |
312 |
|
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4.2.2 Current Applications and Suitability of Smart Devices in Production |
313 |
|
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4.2.3 Potentials for Increased Productivity and New Applications |
314 |
|
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5 Prerequisites and Requirements for Cyber-Physical Production Systems in the Resilient Factory |
315 |
|
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5.1 Technical Requirements |
316 |
|
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5.1.1 Decentralized IT Structures |
316 |
|
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5.1.2 Data Security |
317 |
|
|
5.1.3 Modularity of Technical Systems |
317 |
|
|
5.1.4 Fusion of Shopfloor- and Office-IT |
317 |
|
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5.1.5 Integration of People: Socio-Technical Systems |
318 |
|
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5.2 Scientific Requirements |
319 |
|
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5.2.1 Reliability of Adaptive, Learning Systems |
319 |
|
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5.2.2 Integration of Risk Management for Non-deterministic Systems |
319 |
|
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5.2.3 Model-Based Cooperation: Contradictions, Incompleteness, Failures |
320 |
|
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5.2.4 Emergent Patters |
320 |
|
|
5.2.5 Conflicting Data and Information |
320 |
|
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6 Conclusion |
321 |
|
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References |
322 |
|
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Communication and Networking |
324 |
|
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12 Communication and Networking for the Industrial Internet of Things |
325 |
|
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1 Introduction |
325 |
|
|
2 Communication in Industrial Automation |
326 |
|
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2.1 Definitions |
326 |
|
|
2.2 Current Trends in Industrial Communications |
328 |
|
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2.3 Challenges for the Industrial Internet of Things |
329 |
|
|
3 Communication Within a Local Automation Cell |
330 |
|
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3.1 Diversity Schemes |
331 |
|
|
3.1.1 Frequency Diversity |
331 |
|
|
3.1.2 Time Diversity |
332 |
|
|
3.1.3 Spatial Diversity |
332 |
|
|
3.2 Medium Access Control |
333 |
|
|
3.2.1 Performance Metrics with Regard to the IIoT |
333 |
|
|
3.2.2 Example: IEEE 802.15.4 |
334 |
|
|
4 Communication Within the Factory Hall and Beyond |
335 |
|
|
4.1 Routing and Addressing Background |
336 |
|
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4.2 Challenges for Routing and Addressing in the IIoT |
338 |
|
|
4.2.1 IPv6 and 6LoWPAN |
339 |
|
|
4.3 Addressing and Routing in Standardized Protocol Stacks |
340 |
|
|
5 Application Layer Communication |
344 |
|
|
5.1 The Constrained Application Protocol |
345 |
|
|
5.1.1 The Block Mode |
346 |
|
|
5.1.2 The Observer Mode |
348 |
|
|
5.1.3 CoAP and Proxies |
348 |
|
|
5.2 Cloud and Distributed Processing |
350 |
|
|
6 Conclusion and Outlook |
350 |
|
|
References |
351 |
|
|
13 Communications for Cyber-Physical Systems |
355 |
|
|
1 Introduction |
355 |
|
|
2 Data Communication Networks |
357 |
|
|
3 Types of Communication Networks for CPSs |
360 |
|
|
4 Impact of Communication Network Deficiencies |
363 |
|
|
5 Reliable Communications Within CPSs |
365 |
|
|
6 Approaches to Improve Communications Reliability |
366 |
|
|
6.1 Network Provided QoS Provisioning |
367 |
|
|
6.2 Redundancy |
367 |
|
|
6.3 New Network Generations |
368 |
|
|
7 CPS Communications Using the Internet |
369 |
|
|
8 Communication Standards for CPSs |
371 |
|
|
9 Communication Patterns for CPSs |
374 |
|
|
9.1 Request-Response |
375 |
|
|
9.2 Discovery |
375 |
|
|
9.3 Publish-Subscribe |
376 |
|
|
10 Conclusion |
376 |
|
|
References |
377 |
|
|
Artificial Intelligence and Data Analytics for Manufacturing |
381 |
|
|
14 Application of CPS in Machine Tools |
382 |
|
|
1 Motivation for CPS in the Manufacturing Environment |
382 |
|
|
2 State of the Art—Literature Review |
384 |
|
|
2.1 Characteristics of Cyber-Physical Systems in Manufacturing |
384 |
|
|
2.2 Classification of Intelligent Objects in the Machining Process |
385 |
|
|
2.3 Definition of “Real Time” in the Context of Manufacturing |
388 |
|
|
2.4 Derivation of Requirements |
389 |
|
|
3 Approach to Information Distribution |
390 |
|
|
4 Solutions in the Area of Machining |
392 |
|
|
4.1 Intelligent Chuck for Turning Machine |
392 |
|
|
4.1.1 Phase I: Company Management Level—Analysis of the Turning Process |
393 |
|
|
4.1.2 Phase II: Production Management Level—Scheduling and Situational Production Control |
393 |
|
|
4.1.3 Phase III: Shop Floor—Development of a Chuck Control |
394 |
|
|
4.2 Intelligent Milling Tool |
395 |
|
|
4.2.1 Phase I: Company Management Level—Smart Analytics |
396 |
|
|
4.2.2 Phase II: Production Management Level—Automatic Configuration |
397 |
|
|
4.2.3 Phase III: Shop Floor—Development of the Intelligent Tool |
399 |
|
|
5 Evaluation and Classification |
401 |
|
|
5.1 Validation of the Developed CPS |
401 |
|
|
5.2 Evaluation of the Defined Requirements |
403 |
|
|
5.3 Classification of the Developed Solutions |
404 |
|
|
6 Summary |
405 |
|
|
References |
405 |
|
|
15 Going Smart—CPPS for Digital Production |
408 |
|
|
1 Introduction |
408 |
|
|
2 Technology Knowledge for Digital Production |
409 |
|
|
2.1 Sensors—Perception Organs of CPPS |
410 |
|
|
2.1.1 Concepts of Sensor Integration and Fusion |
411 |
|
|
2.1.2 Applications in Production Environments |
413 |
|
|
2.2 CPPS—The Architecture for Smart Applications |
420 |
|
|
2.2.1 Technology Models—Knowledge Carriers of Production Entities |
421 |
|
|
2.2.2 Tech Apps—The CPPS Human Machine Interface |
423 |
|
|
3 Summary |
426 |
|
|
Acknowledgments |
428 |
|
|
References |
428 |
|
|
16 Manufacturing Cyber-Physical Systems (Industrial Internet of Things) |
430 |
|
|
1 Introduction |
430 |
|
|
2 Preconditions and Standards |
431 |
|
|
3 Challenges |
433 |
|
|
3.1 Steps During the Tank Wagon Loading |
433 |
|
|
3.2 Activities on Top of the Filling Plant |
434 |
|
|
3.3 Activities on the Underside of the Filling Plant |
434 |
|
|
3.4 Opening of the Tank Wagon |
435 |
|
|
4 Requirements from the Manual Process to the Automation |
436 |
|
|
5 Solution Concept (Available Technologies, Intelligent IT, CPS Development) |
437 |
|
|
5.1 Structure of the System |
437 |
|
|
5.2 Process of the Automatic Opening of the Dome Cover |
438 |
|
|
5.3 Vision System |
439 |
|
|
5.4 Gripper System |
441 |
|
|
5.5 Robot System |
441 |
|
|
5.6 Security System |
442 |
|
|
5.6.1 Risks |
442 |
|
|
5.6.2 Technical and Complementary Protective Actions |
443 |
|
|
5.7 Total System: Dome Cover Opening System |
444 |
|
|
5.8 Flow and Operating Concept |
447 |
|
|
6 Research Challenges |
448 |
|
|
7 Conclusions |
450 |
|
|
References |
451 |
|
|
17 Cyber-Physical System Intelligence |
453 |
|
|
1 Introduction |
453 |
|
|
2 Autonomy of Cyber-Physical Systems (CPS) in a Smart Factory |
455 |
|
|
2.1 Components for CPS Autonomy |
455 |
|
|
3 Achieving CPS Autonomy in Smart Factories |
458 |
|
|
4 The RoboCup Logistics League (RCLL) |
462 |
|
|
5 Case Studies on Task-Level Executives for the RCLL |
464 |
|
|
5.1 CLIPS-Based Agent Program |
464 |
|
|
5.2 OpenPRS |
467 |
|
|
5.3 YAGI |
469 |
|
|
5.4 Common Behavioral Architecture |
469 |
|
|
6 Evaluation |
470 |
|
|
6.1 RoboCup 2014 Evaluation Using the CLIPS-Based Agent |
470 |
|
|
6.2 Automated Simulation Tournament for CLIPS and OpenPRS |
472 |
|
|
7 Conclusion |
474 |
|
|
Acknowledgments |
474 |
|
|
References |
475 |
|
|
18 Big Data and Machine Learning for the Smart Factory—Solutions for Condition Monitoring, Diagnosis and Optimization |
479 |
|
|
1 Introduction |
479 |
|
|
2 Big Data in CPSs |
480 |
|
|
3 Requirements and Challenges to Data Quality |
482 |
|
|
4 Condition Monitoring and Diagnosis |
483 |
|
|
4.1 Anomaly Detection Using Identified Hybrid Timed Automata |
483 |
|
|
4.2 Identification of Behavior Models Using Map/Reduce Technology |
484 |
|
|
4.3 Condition Monitoring in Continuous Processes |
485 |
|
|
5 System Optimization |
487 |
|
|
6 Smart Services and Applications |
488 |
|
|
7 Summary and Outlook |
490 |
|
|
References |
491 |
|
|
19 Overview of the CPS for Smart Factories Project: Deep Learning, Knowledge Acquisition, Anomaly Detection and Intelligent User Interfaces |
492 |
|
|
1 Introduction |
492 |
|
|
2 Technical Infrastructure |
493 |
|
|
2.1 Deep Learning |
494 |
|
|
2.2 Knowledge Acquisition |
495 |
|
|
2.3 Anomaly Detection |
496 |
|
|
2.4 Intelligent User Interfaces |
498 |
|
|
3 Use Cases |
501 |
|
|
3.1 Industrial Robots and Anomaly Modeling |
501 |
|
|
3.2 Anomaly Treatment in the Steel Domain |
502 |
|
|
3.3 Outlook: Anomaly Detection in the Energy Domain |
505 |
|
|
Acknowledgments |
507 |
|
|
References |
507 |
|
|
20 Applying Multi-objective Optimization Algorithms to a Weaving Machine as Cyber-Physical Production System |
510 |
|
|
1 Introduction |
510 |
|
|
2 Approach and Implementation of Multi-objective Self-optimization Procedure |
512 |
|
|
2.1 Signal Processing |
512 |
|
|
2.2 Measurement Technology of Warp Tension |
514 |
|
|
2.3 Measurement Technology for Energy Consumption |
514 |
|
|
2.3.1 Air Consumption Measurement |
514 |
|
|
2.3.2 Active Power Measurement |
514 |
|
|
2.3.3 Measurement Technology for Fabric Quality |
515 |
|
|
2.4 Program Steps |
515 |
|
|
3 Desirability Functions and Nelder/Mead Algorithm |
516 |
|
|
3.1 Desirability Functions |
516 |
|
|
3.2 Nelder/Mead Algorithm |
517 |
|
|
3.3 Experimental Results |
518 |
|
|
4 Conclusion and Outlook |
521 |
|
|
References |
521 |
|
|
21 Cyber Physical Production Control |
523 |
|
|
1 Current Challenges of Production Control |
523 |
|
|
2 Vision of a Cyber Physical Production Control |
525 |
|
|
2.1 Smart Decision Support in Daily Life |
525 |
|
|
2.2 Enabler for Decision Support Systems in Production Control |
526 |
|
|
2.2.1 Cyber-Physical Systems |
526 |
|
|
2.2.2 Fast Mobile Internet Infrastructure |
527 |
|
|
2.2.3 Automatic Model Generation in Simulation Software |
528 |
|
|
3 Data Analytics Enable Cyber Physical Production Control |
529 |
|
|
3.1 Data Quality as an Enabler of Cyber Physical Production Control |
532 |
|
|
3.2 Descriptive Analytics |
534 |
|
|
3.3 Diagnostic Analytics |
535 |
|
|
3.4 Predictive Analytics |
537 |
|
|
3.5 Prescriptive Analytics |
538 |
|
|
3.6 Adjusting Production |
539 |
|
|
4 Summary and Outlook |
539 |
|
|
Acknowledgments |
540 |
|
|
References |
540 |
|
|
22 A Versatile and Scalable Production Planning and Control System for Small Batch Series |
544 |
|
|
1 Introduction |
544 |
|
|
1.1 Industry 4.0 Based on Cyber-Physical Systems |
546 |
|
|
1.2 Smart Factory Versus Smart Logistics |
547 |
|
|
1.3 Area of Conflict: Deterministic Planning Versus Decentralized Control |
548 |
|
|
1.4 Overview of Structure |
549 |
|
|
2 Conceptual Approach |
549 |
|
|
3 Exploiting Flexibility Potentials |
552 |
|
|
4 Production Planning |
555 |
|
|
5 Production Control |
557 |
|
|
6 Conclusion and Outlook |
559 |
|
|
Acknowledgments |
560 |
|
|
References |
560 |
|
|
Evolution of Workforce and Human-Machine Interaction |
563 |
|
|
23 CPS and the Worker: Reorientation and Requalification? |
564 |
|
|
1 Enter the Process Worker |
564 |
|
|
2 The Opening of the Lights-Out Factory |
565 |
|
|
3 What Skills Now? |
566 |
|
|
4 The (Temporary?) Return of the Gods |
567 |
|
|
5 The New Factory: Connecting the Dots |
568 |
|
|
6 Worker and Management: Converging Roles? |
570 |
|
|
7 Conclusion: Moving up the Ladder |
571 |
|
|
References |
573 |
|
|
24 Towards User-Driven Cyber-Physical Systems—Strategies to Support User Intervention in Provisioning of Information and Capabilities of Cyber-Physical Systems |
576 |
|
|
1 Introduction |
576 |
|
|
2 Background |
578 |
|
|
2.1 Cyber-Physical Systems |
578 |
|
|
2.2 Solutions for User Intervention in Cyber-Physical Systems |
579 |
|
|
2.3 Architectures for Cyber-Physical Systems |
580 |
|
|
2.4 Requirements of User Intervention for Cyber-Physical System Architecture |
581 |
|
|
3 Example—A User-Driven Cyber Physical Production System |
581 |
|
|
4 Strategies for User-Driven Cyber-Physical Systems |
584 |
|
|
4.1 Strategies for User Intervention in Behaviour of CPS |
585 |
|
|
4.2 Strategies for User Intervention in Behaviour of Supporting Services |
586 |
|
|
5 Architecture for a User-Driven Cyber-Physical System |
588 |
|
|
5.1 End User Viewpoint |
588 |
|
|
5.2 CPS Developer Viewpoint |
590 |
|
|
6 Discussion |
591 |
|
|
7 Conclusions |
593 |
|
|
References |
593 |
|
|
25 Competence Management in the Age of Cyber Physical Systems |
595 |
|
|
1 Companies in the Age of Industrie 4.0 |
595 |
|
|
2 Cyber Physical Systems |
597 |
|
|
3 Competencies and Competence Management |
599 |
|
|
3.1 Defining Individual and Organizational Competencies |
599 |
|
|
3.2 Classification and Measuring of Competencies |
601 |
|
|
3.2.1 Competence Classification |
601 |
|
|
3.2.2 Competence Measurement |
602 |
|
|
4 Consequences and New Competence Requirements for Employees Through CPS Complexity |
604 |
|
|
5 Development of a Measurement Instrument for Competencies in the Age of CPS |
608 |
|
|
6 Conclusions |
610 |
|
|
References |
610 |
|
|
Adjacent Fields and Ecosystems |
615 |
|
|
26 Cyber-Physical Systems for Agricultural and Construction Machinery—Current Applications and Future Potential |
616 |
|
|
1 Introduction |
616 |
|
|
2 Challenges |
617 |
|
|
2.1 Challenges in Agricultural Machinery |
618 |
|
|
2.2 Challenges in Construction Machinery |
619 |
|
|
3 CPS for Mobile Machines |
619 |
|
|
4 Data |
621 |
|
|
5 Key Technologies |
623 |
|
|
6 Key Algorithms |
625 |
|
|
7 Exemplary Processes |
628 |
|
|
7.1 Construction Process |
628 |
|
|
7.1.1 Conclusion CPS in Construction Machinery and Future Potential |
632 |
|
|
7.2 Agricultural Process |
633 |
|
|
7.2.1 Conclusion CPS in Agricultural Machinery and Future Potential |
636 |
|
|
8 Conclusion |
637 |
|
|
References |
638 |
|
|
27 Application of CPS Within Wind Energy—Current Implementation and Future Potential |
645 |
|
|
1 Motivation |
645 |
|
|
2 Potential in Wind Energy |
648 |
|
|
2.1 Wind Turbine |
649 |
|
|
2.2 Wind Farm |
649 |
|
|
2.3 Grid and Local Smart Grid |
650 |
|
|
2.4 Community Interests |
651 |
|
|
3 CPS in Wind Energy |
651 |
|
|
3.1 Current Applications of CPS in Wind Energy |
652 |
|
|
3.1.1 Condition Monitoring System |
652 |
|
|
3.1.2 Supervisory Control and Data Acquisition |
653 |
|
|
3.1.3 Smart Grid and the Integration of Wind Energy |
654 |
|
|
3.1.4 Interaction of Wind Energy and Storage Systems |
655 |
|
|
3.2 Future CPS in Wind Energy |
657 |
|
|
3.2.1 Wind Turbine/Farm |
657 |
|
|
3.2.2 Wind Data |
659 |
|
|
3.2.3 Supply Predictor |
660 |
|
|
3.2.4 Operation and Condition Analyzer |
660 |
|
|
3.2.5 Demand Predictor/Power Requirement |
661 |
|
|
3.2.6 Storage |
661 |
|
|
3.2.7 Electricity Exchange |
662 |
|
|
3.2.8 Community Interests |
663 |
|
|
3.2.9 Central Analyzer and Optimizer |
663 |
|
|
3.2.10 Operation and Maintenance Controller |
664 |
|
|
3.2.11 Energy Controller |
665 |
|
|
4 Outlook and Conclusions |
666 |
|
|
References |
666 |
|
|
28 Transfer Printing for Cyber-Manufacturing Systems |
669 |
|
|
1 Introduction |
669 |
|
|
2 Fundamentals of Transfer Printing |
670 |
|
|
2.1 Basic Concepts in Transfer Printing |
671 |
|
|
2.2 Advanced Transfer Printing Techniques |
673 |
|
|
3 Opportunities of Transfer Printing for Cyber-Manufacturing Systems |
675 |
|
|
3.1 Stretchable Electronics |
676 |
|
|
3.2 Dissolvable Electronics |
677 |
|
|
3.3 Opportunities of Transfer Printing Enabled Devices for Cyber-Manufacturing Systems |
679 |
|
|
4 Challenges of Transfer Printing for Cyber-Manufacturing Systems |
680 |
|
|
5 Future Scope |
683 |
|
|
Acknowledgments |
684 |
|
|
References |
684 |
|
|
29 Advanced Manufacturing Innovation Ecosystems: The Case of Massachusetts |
689 |
|
|
1 Introduction |
689 |
|
|
2 Definition of Key Terms |
691 |
|
|
3 Trends in Advanced Manufacturing |
693 |
|
|
4 The Competitive Position of Manufacturing in Massachusetts |
694 |
|
|
5 The Massachusetts Manufacturing Innovation Ecosystem |
697 |
|
|
5.1 OEMs Within the Manufacturing Innovation Ecosystem |
699 |
|
|
5.2 SMEs Within the Manufacturing Innovation Ecosystem |
701 |
|
|
5.3 Universities in the Manufacturing Innovation Ecosystem |
703 |
|
|
5.4 Startups in the Manufacturing Innovation Ecosystem |
705 |
|
|
6 Manufacturing Intermediaries |
707 |
|
|
7 Recommendations to Improve the Innovation Ecosystem |
708 |
|
|
7.1 Advanced Manufacturing Strategy and Agenda |
708 |
|
|
7.2 Collaboration with OEMs to Drive Innovation and Upgrade SME Capabilities |
709 |
|
|
7.3 Technological and Managerial Support for Innovation in SMEs |
709 |
|
|
7.4 Connections Between Startups and the Innovation Ecosystem |
710 |
|
|
8 Conclusion |
711 |
|
|
References |
712 |
|
|
30 Erratum to: Industrial Internet of Things |
714 |
|
|
Erratum to: |
714 |
|