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Title: A state-of-the-art survey on Augmented Reality-assisted Digital Twin for futuristic human-centric industry transformation
Authors: Yin, Y 
Zheng, P 
Li, C 
Wang, L
Issue Date: Jun-2023
Source: Robotics and computer - integrated manufacturing, June 2023, v. 81, 102515
Abstract: The combination of Augmented Reality (AR) and Digital Twin (DT) has begun to show its potential nowadays, leading to a growing research interest in both academia and industry. Especially under the current human-centric trend, AR embraces the potential to integrate operators into the new generation of Human Cyber–Physical System (HCPS), in which DT is a pillar component. Some review articles have focused on this topic and discussed the benefits of combining AR and DT, but all of them are limited to a specific domain. To fill the gap, this research conducts a state-of-the-art survey (till 17-July-2022) from the AR-assisted DT perspective across different sectors of the industrial field, covering a total of 118 selected publications. Firstly, application scenarios and functions of AR-assisted DT are summarized by following the engineering lifecycle, among which production process, service design, and Human–Machine Interaction (HMI) are hot topics. Then, improvements specifically brought by AR are analyzed according to three dimensions, namely virtual twin, hybrid twin, and cognitive twin, respectively. Finally, challenges and future perspectives of AR-assisted DT for futuristic human-centric industry transformation are proposed, including promoting product design, robotic-related works, cyber–physical interaction, and human ergonomics.
Keywords: Augmented reality
Digital twin
Human cyber–physical system
Human–machine interaction
Smart manufacturing
Publisher: Elsevier Ltd
Journal: Robotics and computer - integrated manufacturing 
ISSN: 0736-5845
EISSN: 1879-2537
DOI: 10.1016/j.rcim.2022.102515
Rights: © 2022 Elsevier Ltd. All rights reserved.
© 2022. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/
The following publication Yin, Y., Zheng, P., Li, C., & Wang, L. (2023). A state-of-the-art survey on Augmented Reality-assisted Digital Twin for futuristic human-centric industry transformation. Robotics and Computer-Integrated Manufacturing, 81, 102515 is available at https://doi.org/10.1016/j.rcim.2022.102515.
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