Andrew Nee

Prof. Andrew Nee

Department of Mechanical Engineering, National University of Singapore, 9 Engineering Drive 1, Singapore 117576, Singapore

Research Focus & Metrics

Academic Career Length

34Years (1993-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 October 2018 in IEEE Transactions on Industrial Informatics
Verified
Journal Article
Closed access
Fei TaoFei Tao
Fei Tao
HZHe Zhang
He Zhang
ALAng Liu
Ang Liu
Andrew NeeAndrew Nee
Andrew Nee
Digital twin (DT) is one of the most promising enabling technologies for realizing smart manufacturing and Industry 4.0. DTs are characterized by the seamless integration between the cyber and physical spaces. The importance of DTs is increasingly recognized by both academia and industry. It has been almost 15 years since the concept of the DT was initially proposed. To date, many DT applications have been successfully implemented in different industries, including product design, production, prognostics and health management, and some other fields. However, at present, no paper has focused on the review of DT applications in industry. In an effort to understand the development and application of DTs in industry, this paper thoroughly reviews the state-of-the-art of the DT research concerning the key components of DTs, the current development of DTs, and the major DT applications in industry. This paper also outlines the current challenges and some possible directions for future work.

1 January 2021 in Journal of Manufacturing Systems
Verified
Journal Article
Closed access
QQQinglin Qi
Qinglin Qi
Fei TaoFei Tao
Fei Tao
THTianliang Hu
Tianliang Hu
Nabil AnwerNabil Anwer
Nabil Anwer
ALAng Liu
Ang Liu
Andrew NeeAndrew Nee
Andrew Nee


25 February 2018 in International Journal of Production Research
Verified
Journal Article
Closed access
Fei TaoFei Tao
Fei Tao
FSFangyuan Sui
Fangyuan Sui
ALAng Liu
Ang Liu
QQQinglin Qi
Qinglin Qi
MZMeng Zhang
Meng Zhang
Andrew NeeAndrew Nee
Andrew Nee
With the advent of new generation information technologies in industry and product design, the big data-driven product design era has arrived. However, the big data-driven product design mainly places emphasis on the analysis of physical data rather than the virtual models, in other words, the convergence between product physical and virtual space is usually absent. Digital twin, a new emerging and fast growing technology which connects the physical and virtual world, has attracted much attention worldwide recently. This paper presents a new method for product design based on the digital twin approach. The development of product design is briefly introduced first. The framework of digital twin-driven product design (DTPD) is then proposed and analysed. A case is presented to illustrate the application of the proposed DTPD method.

1 January 2018 in CIRP Annals
Verified
Journal Article
Closed access
Fei TaoFei Tao
Fei Tao
MZMeng Zhang
Meng Zhang
Yushan LiuYushan Liu
Yushan Liu
Andrew NeeAndrew Nee
Andrew Nee

1 January 2012 in CIRP Annals
Verified
Journal Article
Closed access
Andrew NeeAndrew Nee
Andrew Nee
SK OngSK Ong
SK Ong
GCG. Chryssolouris
G. Chryssolouris
Dimitris MourtzisDimitris Mourtzis
Dimitris Mourtzis