Digital Twin Driven Service
Coordonnateurs : Tao Fei, Qi Qinglin, Nee A.Y.C.
Digital Twin Driven Smart Service draws on the latest industry practice and research to explain how to implement digital twin service in a range of scenarios. It addresses relevant theory and methodologies, including product service, prognostic health management service, energy efficient service and testing service. Other sections discuss key enabling technologies supported by cutting-edge case studies of implementation. Drawing on the work of researchers at the forefront of this technology, this book is the ideal guide for anyone interested in product services, manufacturing services and digital twin services.
This book is one part of a trilogy on digital twins, the other titles being Digital Twin Driven Smart Design and Digital Twin Driven Smart Manufacturing.
1. From Service to Digital Twin Service 2. Digital Twin Driven Service Collaboration 3. Digital Twin-driven Production Line Custom Design Service 4. Digital twin-enhanced product family design and optimization service 5. Digital Twin Driven Fault Diagnosis Service of Rotating Machinery 6. Digital Twin Driven Energy-Efficient Assessment Service 7. Digital Twin Driven Cutting Tool Service 8. Digital Twin Driven Prognostics and Health Management 9. Production Process Management for Intelligent Coal Mining Based on Digital Twin 10. Digital Twin Enhanced Tribo-test Service
Qinglin Qi is a Hong Kong scholar supported by both the School of Automation Science and Electrical Engineering, Beihang University, and Department of Industrial Systems Engineering, The Hong Kong Polytechnic University. His research interests are service-oriented smart manufacturing, digital twin driven manufacturing and service.
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.
- Provides a wide range of applications, including tribological testing, cutting tool service and energy efficiency assessment
- Explains everything needed to understand and implement digital twin models for service, including frameworks, theories and technologies
- Explores future challenges for research in this area, including the ongoing standardization of digital twin technology
Date de parution : 03-2022
Ouvrage de 326 p.
15.2x22.8 cm
Thèmes de Digital Twin Driven Service :
Mots-clés :
Auxiliary maintenance; Bayesian network; Coal mine equipment; Customized design; Cutting tool selection service; Cutting tool service availability; Data synchronization; Design optimization; Digital twin; Digital twin as services; Digital twin enhanced services; Digital twin services applications; Digital twin-driven services; Digitalization; DT-driven cutting tool service; Energy consumption prediction; Energy-efficient assessment; Failure prediction; Fault diagnosis; Individual needs; Industrial internet of things; Manufacturing capability; Manufacturing service; Particle filter; Physical analysis; Product and service system; Product family design; Production line design; Prognostic and health management; Prognostics and health management; Remaining useful life prediction service; Remote control; Rotating machinery; Service collaboration; Service optimization; Services; Servitization; Smart manufacturing
