DigiTwin: An Approach for Production Process Optimization in a Built Environment (Springer Series in Advanced Manufacturing)

✍ Scribed by Josip Stjepandić (editor), Markus Sommer (editor), Berend Denkena (editor)

• Publisher: Springer
• Year: 2021
• Tongue: English
• Leaves: 264
• Category: Library

✦ Synopsis

The focus of this book is an application of Digital Twin as a concept and an approach, based on the most accurate view on a physical production system and its digital representation of complex engineering products and systems. It describes a methodology to create and use Digital Twin in a built environment for the improvement and optimization of factory processes such as factory planning, investment planning, bottleneck analysis, and in-house material transport. The book provides a practical response based on achievements of engineering informatics in solving challenges related to the optimization of factory layout and corresponding processes.

This book introduces the topic, providing a foundation of knowledge on process planning, before discussing the acquisition of objects in a factory and the methods for object recognition. It presents process simulation techniques, explores challenges in process planning, and concludes by looking at future areas of progression. By providinga holistic, trans-disciplinary perspective, this book will showcase Digital Twin technology as state-of-the-art both in research and practice.

✦ Table of Contents

Acknowledgment
Used Trademarks
Contents
Editors and Contributors
1 Introduction to the Book
1.1 Origins of the Digital Twin
1.2 Origins of the Book
1.3 Goals of the Book
1.4 Audience
1.5 Content of the Book
1.6 Contributors of the Book
References
2 Requirements for the Optimization of Processes Using a Digital Twin of Production Systems
2.1 Introduction
2.2 Investigated Use Cases
2.3 Parameters for the Framework of the Digital Twin
2.4 Parameter Properties for Implementation in the Digital Twin
2.5 Summary and Outlook
Appendix
References
3 Digital Twin: A Conceptual View
3.1 Introduction
3.2 Taxonomy of Digital Twin
3.3 Conception of Digital Twin
3.3.1 Digital Master
3.3.2 Digital Manufacturing Twin
3.3.3 Digital Instance Twin
3.4 Main Expressions of Digital Twin in Context of Industry 4.0
3.5 Simulations as the Backbone of the Digital Twin
3.6 Proposed Approach
3.7 Summary and Further Research
References
4 Scan Methods and Tools for Reconstruction of Built Environments as Basis for Digital Twins
4.1 Introduction
4.2 Requirements for Acquisition of Shape and Position of Physical Objects in a Factory
4.2.1 Requirements for the Scan of Manufacturing Facilities
4.2.2 Requirements from a Production Point of View
4.3 Acquisition Approaches in a Comparative View
4.3.1 Laser Scanner
4.3.2 Photogrammetry
4.3.3 Comparison of the Different Steps in Generating a Point Cloud by Photogrammetry or Laser Scanner
4.3.4 Application of the Different Technologies
4.4 SLAM, Structure from Motion, Photogrammetry
4.4.1 Photogrammetry
4.4.2 Structure from Motion (SfM)
4.4.3 Simultaneous Localization and Mapping (SLAM)
4.5 Image-Based 3D Reconstruction
4.5.1 Step 1: Feature Extraction
4.5.2 Step 2: Correspondence Generation
4.5.3 Step 3: 3D Reconstruction
4.6 3D Reconstruction in Production Environments
4.6.1 Definition of the Test Environment
4.6.2 Monocular Method
4.6.3 Stereo Images (Stereo Camera)
4.6.4 Spherical Images
4.7 Conclusions and Outlook
References
5 Machine Learning in Manufacturing in the Era of Industry 4.0
5.1 Introduction
5.2 Fundamental and Problems Concepts
5.2.1 When Is Machine Learning Used?
5.2.2 Where Are Evolutionary Algorithms Used?
5.2.3 A Combination of Several Methods of AI?
5.2.4 Procedure for Creating a Behavioral Model/Digital Twin
5.3 Gains of Machine Learning
5.3.1 Efficient Derivation of the Model Configuration Based on the Data
5.3.2 Generating Behavioral Model Through Training with Data
5.3.3 Easy Validation of the Model
5.3.4 Optimization of the Real System Based on the Model
5.4 Use Cases in Plant Engineering
5.4.1 Mechanical Model of a Pneumatic Cylinder
5.4.2 Forecast Models Solar System
5.5 Data Analysis
5.6 Discussion
5.7 Conclusions and Outlook
References
6 Object Recognition Methods in a Built Environment
6.1 Introduction
6.2 Methodology for Object Recognition
6.2.1 Challenges in Object Recognition
6.2.2 Image-Oriented Methods
6.2.3 Point Cloud-Oriented Methods
6.2.4 Video-Oriented Methods
6.3 Approaches for Point Cloud Generation
6.4 Test Base
6.5 Impact of Data Acquisition Accuracy
6.6 Methods for Point Cloud Processing
6.6.1 Point Cloud Preprocessing
6.6.2 Mesh Reconstruction
6.6.3 Point Cloud Segmentation
6.6.4 Point Cloud Modeling
6.7 Comparison of Recognition Methods
6.8 Application of Methods
6.9 Discussion and Future Perspectives
6.10 Conclusions and Outlook
References
7 Data Quality Management for Interoperability
7.1 Introduction
7.2 Digital Thread
7.3 Data Quality Classification
7.3.1 Data Quality Dimensions
7.3.2 Related Standards
7.4 Data Quality Metrics
7.5 Practical Examples
7.5.1 Design
7.5.2 Manufacturing
7.5.3 Data Migration
7.6 Discussion and Future Perspectives
7.7 Conclusions and Outlook
References
8 Object Recognition Findings in a Built Environment
8.1 Introduction
8.2 Process Design
8.3 Automation of Workflow
8.4 Model Preparation
8.5 Model Segmentation
8.6 Training and Testing, Rebuild of Structures
8.7 Discussion
8.8 Conclusions and Outlook
References
9 Design of Simulation Models
9.1 Introduction
9.2 Ontology of Production Systems
9.2.1 Ontology-Based Information System for Generating Simulations of Production Systems
9.2.2 Information System for the Description of Production Systems
9.2.3 Exemplary Applications
9.3 Data Model
9.4 Model Design
9.4.1 Design of the Functional Model
9.4.2 Design of the Graphical Model
9.5 Results and Summary
References
10 The Commercialization of Digital Twin by an Extension of a Business Ecosystem
10.1 Introduction
10.2 Supplier Networks, Engineering Collaboration and Network-Centric Operations
10.3 Shift from Product to Service Platform and Ecosystem
10.4 The Rise of OpenDESC.Com
10.5 Use Cases of OpenDESC.Com
10.5.1 CAD Data Translation
10.5.2 CAD Data Migration
10.5.3 Data Transfer
10.5.4 Intellectual Property Protection
10.5.5 Portal Services
10.6 Planning of Extension by Enterprise Architecture Integration
10.7 Adoption of Extended Services
10.7.1 Working Procedure
10.7.2 Input and Outcome
10.8 Adoption of Digital Twin Offering
10.9 Discussion
10.10 Conclusions and Outlook
References
11 Digital Twin: Conclusion and Future Perspectives
11.1 Introduction
11.2 Further Developments of DigiTwin Solution
11.2.1 Parameter-Based Updating of the Digital Twin
11.2.2 Structural Partial Update of the Digital Twin
11.2.3 Structural Update of the Digital Twin
11.3 Self-X Digital Twin on Backend
11.4 Self-X Digital Twin on Edge-Devices
11.5 Trends in Digital Twin
11.6 Challenges in Digital Twin
11.7 Closing Remarks and Conclusions
References