Digital Twin Driven Smart Manufacturing
This book examines the background, latest research, and application models for digital twin technology, and shows how it can be central to a smart manufacturing process. The interest in digital twin in manufacturing is driven by a need for excellent product reliability, and an overall trend towards...
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| Language: | English |
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Chantilly
Elsevier
2019
Elsevier Science & Technology Academic Press |
| Edition: | 1 |
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| ISBN: | 9780128176306, 012817630X |
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| Abstract | This book examines the background, latest research, and application models for digital twin technology, and shows how it can be central to a smart manufacturing process. The interest in digital twin in manufacturing is driven by a need for excellent product reliability, and an overall trend towards intelligent, and connected manufacturing systems. This book provides an ideal entry point to this subject for readers in industry and academia, as it answers the questions: (a) What is a digital twin? (b) How to construct a digital twin? (c) How to use a digital twin to improve manufacturing efficiency? (d) What are the essential activities in the implementation of a digital twin? (e) What are the most important obstacles to overcome for the successful deployment of a digital twin? (f) What are the relations between digital twin and New Technologies? (g) How to combine digital twin with the New Technologies to achieve high efficiency and smartness in manufacturing? |
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| AbstractList | This book examines the background, latest research, and application models for digital twin technology, and shows how it can be central to a smart manufacturing process. The interest in digital twin in manufacturing is driven by a need for excellent product reliability, and an overall trend towards intelligent, and connected manufacturing systems. This book provides an ideal entry point to this subject for readers in industry and academia, as it answers the questions: (a) What is a digital twin? (b) How to construct a digital twin? (c) How to use a digital twin to improve manufacturing efficiency? (d) What are the essential activities in the implementation of a digital twin? (e) What are the most important obstacles to overcome for the successful deployment of a digital twin? (f) What are the relations between digital twin and New Technologies? (g) How to combine digital twin with the New Technologies to achieve high efficiency and smartness in manufacturing? Digital Twin Driven Smart Manufacturing examines the background, latest research, and application models for digital twin technology, and shows how it can be central to a smart manufacturing process. The interest in digital twin in manufacturing is driven by a need for excellent product reliability, and an overall trend towards intelligent, and connected manufacturing systems. This book provides an ideal entry point to this subject for readers in industry and academia, as it answers the questions: (a) What is a digital twin? (b) How to construct a digital twin? (c) How to use a digital twin to improve manufacturing efficiency? (d) What are the essential activities in the implementation of a digital twin? (e) What are the most important obstacles to overcome for the successful deployment of a digital twin? (f) What are the relations between digital twin and New Technologies? (g) How to combine digital twin with the New Technologies to achieve high efficiency and smartness in manufacturing? This book focuses on these problems as it aims to help readers make the best use of digital twin technology towards smart manufacturing. Analyzes the differences, synergies and possibilities for integration between digital twin technology and other technologies, such as big data, service and Internet of ThingsDiscuss new requirements for a traditional three-dimension digital twin and proposes a methodology for a five-dimension versionInvestigates new models for optimized manufacturing, prognostics and health management, and cyber-physical fusion based on the digital twin |
| Author | Nee A. Y. C Tao Fei Zhang Meng |
| Author_xml | – sequence: 1 fullname: Tao, Fei – sequence: 2 fullname: Zhang, Meng – sequence: 3 fullname: Nee, A. Y. C |
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| Copyright | 2019 |
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| DOI | 10.1016/C2018-0-02206-9 |
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| Snippet | This book examines the background, latest research, and application models for digital twin technology, and shows how it can be central to a smart... Digital Twin Driven Smart Manufacturing examines the background, latest research, and application models for digital twin technology, and shows how it can be... |
| SourceID | askewsholts proquest knovel |
| SourceType | Aggregation Database Publisher |
| SubjectTerms | Manufacturing Competitiveness Manufacturing Engineering Manufacturing industries-Technological innovations Manufacturing processes-Automation Process Design, Control & Automation Process Modeling & Simulation Virtual computer systems |
| TableOfContents | Title Page
Preface
Table of Contents
1. Background and Concept of Digital Twin
2. Applications of Digital Twin
3. Five-Dimension Digital Twin Modeling and its Key Technologies
4. Digital Twin Shop-Floor
5. Equipment Energy Consumption Management in Digital Twin Shop-Floor
6. Cyber - Physical Fusion in Digital Twin Shop-Floor
7. Digital Twin-Driven Prognostics and Health Management
8. Digital Twin and Cloud, Fog, Edge Computing
9. Digital Twin and Big Data
10. Digital Twin and Services
11. Digital Twin and Virtual Reality and Augmented Reality/Mixed Reality
12. Digital Twin, Cyber - Physical System, and Internet of Things
Index 10.2.2 Framework of Service-Oriented Smart Manufacturing 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 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 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 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 |
| Title | Digital Twin Driven Smart Manufacturing |
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