A state-of-the-art survey on Augmented Reality-assisted Digital Twin for futuristic human-centric industry transformation. (June 2023)

• Record Type: Journal Article
• Authors: Yin, Yue; Zheng, Pai; Li, Chengxi; Wang, Lihui
• Is Part Of: Robotics and computer-integrated manufacturing. Volume 81(2023)
• Publication Date: 2023-06
• Subjects: Digital twin -- Augmented reality -- Human cyber–physical system -- Human–machine interaction -- Smart manufacturing; Robots, Industrial -- Periodicals; Computer integrated manufacturing systems -- Periodicals; Robotics -- Periodicals; Robots industriels -- Périodiques; Productique -- Périodiques; Robotique -- Périodiques; 670.285
• DOI: 10.1016/j.rcim.2022.102515
• Languages: English
• ISSNs: 0736-5845

Abstract

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. Highlights: AR-assisted DT applications across different sectors of industrial fields are reviewed comprehensively. Enhancement by AR-assisted DT in the whole engineering lifecycle is introduced. The add-on benefits of AR are discussed along three DT dimensions. Challenges and future perspectives of AR-assisted DT are proposed.