Kooperativer Bibliotheksverbund

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Format: 1 online resource (283 pages)

ISBN: 0-12-817631-8

Note: Front Cover -- Digital Twin Driven Smart Manufacturing -- Copyright Page -- Contents -- Preface -- 1 Background and Connotation -- 1 Background and Concept of Digital Twin -- 1.1 Background of the Development of Digital Twin -- 1.2 History of Digital Twin -- 1.3 Concept of Digital Twin -- 1.3.1 Theoretical Definition of Digital Twin -- 1.3.2 Digital Twin in the Views of Enterprises -- 1.3.3 Cores of Digital Twin: Models, Data, Connections, and Services -- 1.4 Digital Twin and Related Concepts -- 1.4.1 Digital Twin and Physical/Virtual Space -- 1.4.2 Digital Twin and Virtual Prototype -- 1.4.3 Digital Twin and PLM -- 1.4.4 Digital Twin and Digital Asset/Enterprise/Industry -- 1.4.5 Digital Twin and Digital Thread -- 1.4.6 Digital Twin and Digital Shadow -- 1.5 Value of Digital Twin -- 1.5.1 Increasing Visibility -- 1.5.2 Reducing Time to Market -- 1.5.3 Keeping Optimal Operation -- 1.5.4 Reducing Energy Consumption -- 1.5.5 Reducing Maintenance Cost -- 1.5.6 Increasing User Engagement -- 1.5.7 Fusing Information Technologies -- 1.6 Summary -- References -- 2 Applications of Digital Twin -- 2.1 Digital Twin in Product Lifecycle -- 2.1.1 Digital Twin in Design Stage -- 2.1.2 Digital Twin in Production Stage -- 2.1.3 Digital Twin in Service Stage -- 2.1.4 Digital Twin Across Multiple Stages -- 2.1.5 Observations -- 2.1.5.1 Production and PHM Are the Most Popular Applied Fields for the DT -- 2.1.5.2 DT Has Attracted the Most Attention in the United States, China, and Europe -- 2.2 Digital Twin in Industrial Applications -- 2.2.1 Digital Twin in Aerospace -- 2.2.2 Digital Twin in Electric Power Generation -- 2.2.3 Digital Twin in Automotive -- 2.2.4 Digital Twin in Oil and Gas -- 2.2.5 Digital Twin in Healthcare and Medicine -- 2.2.6 Digital Twin in Maritime/Shipping -- 2.2.7 Digital Twin in City Management -- 2.2.8 Digital Twin in Agriculture. , 2.2.9 Digital Twin in Construction -- 2.2.10 Digital Twin in Environmental Protection -- 2.2.11 Digital Twin in Security and Emergency -- 2.2.12 Observations -- 2.3 Future Market for Digital Twin -- 2.4 Challenges of Digital Twin Applications -- 2.4.1 Cognitive and Technical Level of People -- 2.4.2 Technology and Infrastructure -- 2.4.3 Support Tools -- 2.4.4 Standards and Specifications -- 2.4.5 Cost Control and Management -- 2.4.6 Cyber Security and Intellectual Property Rights -- 2.4.7 Insufficient Development of Digital Twin -- 2.5 Summary -- References -- 3 Five-Dimension Digital Twin Modeling and Its Key Technologies -- 3.1 Traditional Three-Dimension Digital Twin -- 3.1.1 Three-Dimension Digital Twin -- 3.1.2 Existing Works on Digital Twin Modeling -- 3.2 New Requirements on Digital Twin -- 3.2.1 From Application Aspect: Requiring Wider Application -- 3.2.2 From Technology Aspect: Requiring to Embrace New IT -- 3.2.3 From Modeling Object Aspect: Requiring Data and Services -- 3.2.4 From Modeling Method Aspect: Requiring High-Fidelity Virtual Modeling -- 3.3 Extended Five-Dimension Digital Twin -- 3.3.1 Five-Dimension Digital Twin -- 3.3.2 Physical Entity -- 3.3.3 Virtual Entity -- 3.3.4 Services -- 3.3.5 Digital Twin Data -- 3.3.6 Connection -- 3.4 Application-Oriented Three-Level Digital Twins -- 3.4.1 Unit-Level Digital Twin -- 3.4.2 System-Level Digital Twin -- 3.4.3 System of Systems-Level Digital Twin -- 3.5 Key Technologies for Digital Twin Modeling -- 3.5.1 Key Technologies for Physical Entity Modeling -- 3.5.2 Key Technologies for Virtual Entity Modeling -- 3.5.3 Key Technologies for Services Modeling -- 3.5.4 Key Technologies for Digital Twin Data Modeling -- 3.5.5 Key Technologies for Connection Modeling -- 3.6 Eight Rules for Digital Twin Modeling -- 3.6.1 Data and Knowledge Based -- 3.6.2 Modularization -- 3.6.3 Light Weight. , 3.6.4 Hierarchy -- 3.6.5 Standardization -- 3.6.6 Servitization -- 3.6.7 Openness and Scalability -- 3.6.8 Robustness -- 3.7 Summary -- References -- 2 Digital Twin Driven Smart Manufacturing -- 4 Digital Twin Shop-Floor -- 4.1 Evolution Path of Shop-Floor -- 4.1.1 Production Resource Management -- 4.1.2 Production Activity Planning -- 4.1.3 Production Process Control -- 4.2 Related Works -- 4.2.1 Data Collection -- 4.2.2 Data Processing -- 4.2.3 Information System Construction -- 4.2.4 Virtual Model Construction -- 4.2.5 Exploration of New Modes for Production -- 4.3 Concept of Digital Twin Shop-Floor -- 4.3.1 Concept of Digital Twin Shop-Floor -- 4.3.2 Operation Process of Digital Twin Shop-Floor -- 4.4 Implementation of Digital Twin Shop-Floor -- 4.4.1 Physical Shop-Floor -- 4.4.2 Virtual Shop-Floor -- 4.4.3 Shop-Floor Service System -- 4.4.4 Shop-Floor Digital Twin Data -- 4.5 Characteristics of Digital Twin Shop-Floor -- 4.5.1 Cyber-Physical Fusion -- 4.5.2 Data Driven -- 4.5.3 Fusion of Data From All of the Elements, Processes, and Businesses -- 4.5.4 Iterative Optimization -- 4.6 Key Technologies for Digital Twin Shop-Floor -- 4.7 Challenges for Digital Twin Shop-Floor -- 4.8 Summary -- References -- 5 Equipment Energy Consumption Management in Digital Twin Shop-Floor -- 5.1 Introduction -- 5.2 Framework of EECM in Digital Twin Shop-Floor -- 5.3 Implementation of EECM in Digital Twin Shop-Floor -- 5.3.1 Physical Machine Tool -- 5.3.2 Virtual Machine Tool -- 5.3.3 EECM Services -- 5.3.4 Digital Twin Data -- 5.4 Potential Advantages of EECM in Digital Twin Shop-Floor -- 5.4.1 Advantages in Energy Consumption Monitoring -- 5.4.2 Advantages in Energy Consumption Analysis -- 5.4.3 Advantages in Energy Consumption Optimization -- 5.5 Summary -- References -- 6 Cyber-Physical Fusion in Digital Twin Shop-Floor -- 6.1 Introduction. , 1. Connection and Interconnection on the Shop-Floor -- 2. Digital/Virtual Shop-Floor Modeling/Simulation -- 3. Shop-Floor Data/Information Integration -- 4. Shop-Floor Optimal Operations and Precision Management -- 6.2 Reference Architecture for Digital Twin Shop-Floor -- 6.3 Physical Elements Fusion -- 1 Man-Machine-Material-Environment Smart Connection and Interconnection -- 2 Man-Machine-Material-Environment Smart Communication and Computing -- 3 Man-Machine-Material-Environment Smart Control and Interaction -- 4 Man-Machine-Material-Environment Smart Cooperation and Convergence -- 6.4 Models Fusion -- 1 Construction of the Multidimension Models -- 2 Evaluation and Verification of the Multidimension Models -- 3 Correlation and Mapping Mechanism of the Multidimension Models -- 4 Theory and Method of the Multidimension Models Consistency -- 6.5 Data Fusion -- 1 Data Generation, Modeling, and Cleaning -- 2 Data Correlation, Clustering, and Mining -- 3 Data Iteration, Evolution, and Fusion -- 6.6 Services Fusion -- 1 Data-Driven Service Generation -- 2 Service Smart Management and Optimization -- 3 Service Fusion and Application -- 6.7 Summary -- References -- 7 Digital Twin-Driven Prognostics and Health Management -- 7.1 Introduction -- 7.2 Digital Twin for Complex Equipment -- 7.2.1 Five-Dimension Digital Twin for Complex Equipment -- 7.2.2 Modeling for Each Dimension of Digital Twin -- 7.3 Digital Twin-Driven PHM Method -- 7.3.1 Framework -- 7.3.1.1 Inputs -- 7.3.1.2 Roles of DT -- 7.3.1.3 Outputs -- 7.3.2 Procedure -- 7.3.2.1 Model Calibration -- 7.3.2.2 Inconsistency Caused Judgment -- 7.3.2.3 Identification and Prediction of Fault Cause -- 7.3.3 Coevolution Mechanism -- 7.4 Case Study -- 7.4.1 Problem Description -- 7.4.2 Digital Twin-Driven PHM for Yaw System -- 7.4.3 Digital Twin-Driven PHM for the Gearbox -- 7.5 Summary -- References. , 3 Digital Twin and New Technologies -- 8 Digital Twin and Cloud, Fog, Edge Computing -- 8.1 Introduction -- 8.2 Three-Level Digital Twins in Manufacturing -- 8.3 From Cloud Computing to Fog Computing and Edge Computing -- 8.3.1 Cloud Computing -- 8.3.2 Fog Computing -- 8.3.3 Edge Computing -- 8.4 Three-Level Digital Twins Based on Edge Computing, Fog Computing, and Cloud Computing -- 8.4.1 Unit-Level Digital Twin Based on Edge Computing -- 8.4.2 System-Level Digital Twin Based on Fog Computing -- 8.4.3 System of Systems-Level Digital Twin Based on Cloud Computing -- 8.5 Summary -- References -- 9 Digital Twin and Big Data -- 9.1 Introduction -- 9.2 Big Data -- 9.2.1 Brief History of Big Data -- 9.2.2 Concept of Big Data -- 9.2.3 Characteristics of Big Data -- 9.3 Lifecycle of Big Data in Manufacturing -- 9.3.1 Data Sources -- 9.3.2 Data Collection -- 9.3.3 Data Storage -- 9.3.4 Data Processing -- 9.3.5 Data Visualization -- 9.3.6 Data Transmission -- 9.3.7 Data Application -- 9.4 360° Comparison of Digital Twin and Big Data in Manufacturing -- 9.4.1 Comparison From General Perspective -- 9.4.1.1 Similarities Between Big Data and Digital Twin -- 9.4.1.2 Differences Between Big Data and Digital Twin -- 9.4.2 Comparison From Data Perspective -- 9.4.2.1 Advantages of Big Data Over Digital Twin -- 9.4.2.2 Advantages of Digital Twin Over Big Data -- 9.5 Complementarity Between Big Data and Digital Twin -- 9.6 Fusion of Digital Twin and Big Data in Manufacturing -- 9.6.1 Product Design Driven by Fusion of Digital Twin and Big Data -- 9.6.2 Production Driven by Fusion of Digital Twin and Big Data -- 9.6.3 PHM Driven by Fusion of Digital Twin and Big Data -- 9.7 Summary -- References -- 10 Digital Twin and Services -- 10.1 Introduction -- 10.2 Services in Manufacturing -- 10.2.1 Concept of Servitization in Manufacturing. , 10.2.2 Framework of Service-Oriented Smart Manufacturing.

Additional Edition: ISBN 0-12-817630-X

Language: English