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Andrew Y. C. Nee
Researcher at National University of Singapore
Publications - 433
Citations - 18187
Andrew Y. C. Nee is an academic researcher from National University of Singapore. The author has contributed to research in topics: Augmented reality & Product design. The author has an hindex of 56, co-authored 429 publications receiving 13861 citations. Previous affiliations of Andrew Y. C. Nee include Beihang University & Massachusetts Institute of Technology.
Papers
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Digital Twin in Industry: State-of-the-Art
TL;DR: This paper thoroughly reviews the state-of-the-art of the DT research concerning the key components of DTs, the current development ofDTs, and the major DT applications in industry and outlines the current challenges and some possible directions for future work.
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Digital twin-driven product design framework
Fei Tao,Fangyuan Sui,Ang Liu,Qinglin Qi,Meng Zhang,Boyang Song,Zirong Guo,Stephen C.-Y. Lu,Andrew Y. C. Nee +8 more
TL;DR: This paper presents a new method for product design based on the digital twin approach, which places emphasis on the analysis of physical data rather than the virtual models and illustrates the application of the proposed DTPD method.
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Augmented reality applications in design and manufacturing
TL;DR: The research and development of augmented reality (AR) applications in design and manufacturing is reviewed in this paper, which consists of seven main sections: the background of manufacturing simulation applications and the initial AR developments, current hardware and software tools associated with AR.
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Digital Twins and Cyber–Physical Systems toward Smart Manufacturing and Industry 4.0: Correlation and Comparison
TL;DR: This paper reviews and analyzes CPS and DTs from multiple perspectives, including their origin, development, engineering practices, cyber–physical mapping, and core elements.
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Enabling technologies and tools for digital twin
TL;DR: 5-dimension digital twin model provides reference guidance for understanding and implementing digital twin, and the frequently-used enabling technologies and tools for digital twin are investigated and summarized to provide Technologies and tools references for the applications of digital twin in the future.