Digital Twin Driven Smart 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.

1. Background and Concept of Digital Twin2. Applications of Digital Twin3. Digital Twin Modeling and Its Key Technologies4. Digital Twin Shop-floor (DTS)5. Equipment Energy Consumption Management in Digital Twin Shop-floor6. Cyber-Physical Fusion in Digital Twin Shop-floor7. Digital Twin Driven Prognostics and Health Management (PHM)8. Digital Twin and Cloud, Fog, Edge Computing9. Digital Twin and Big Data10. Digital Twin and Services11. Digital Twin and Virtual Reality, Augmented Reality and Mixed Reality12. Digital Twin and Internet of Things

Fei Tao is a Professor at the School of Automation Science and Electrical Engineering, Beihang University, Beijing, China. His research interests are service-oriented smart manufacturing, manufacturing service management and optimization, digital twin driven product design/manufacturing/service, green and sustainable manufacturing.
Meng Zhang is a PhDd student at the School of Automation Science and Electrical Engineering, Beihang University, Beijing, China. Her research is focused on digital twin technology in manufacturing and sustainable manufacturing.
A.Y.C. Nee is Professor Emeritus in Manufacturing Engineering at the National University of Singapore. His research interests include the use of AI, virtual and augmented reality applications in manufacturing, sustainable product design and life cycle engineering, and computer aided manufacturing design. He is Fellow of CIRP, Fellow of SME and Fellow of the Academy of Engineering Singapore.