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State-of-the-art survey on digital twin implementations

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Abstract

Digital twin (DT) has garnered attention in both industry and academia. With advances in big data and internet of things (IoTs) technologies, the infrastructure for DT implementation is becoming more readily available. As an emerging technology, there are both potential and challenges. DT is a promising methodology to leverage the modern data explosion to aid engineers, managers, healthcare experts and politicians in managing production lines, patient health and smart cities by providing a comprehensive and high fidelity monitoring, prognostics and diagnostics tools. New research and surveys into the topic are published regularly, as interest in this technology is high although there is a lack of standardization to the definition of a DT. Due to the large amount of information present in a DT system and the dual cyber and physical nature of a DT, augmented reality (AR) is a suitable technology for data visualization and interaction with DTs. This paper seeks to classify different types of DT implementations that have been reported, highlights some researches that have used AR as data visualization tool in DT, and examines the more recent approaches to solve outstanding challenges in DT and the integration of DT and AR.

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  1. Department of Mechanical Engineering, National University of Singapore, 9 Engineering Drive 1, Singapore, 117575, Singapore

    Y. K. Liu, S. K. Ong & A. Y. C. Nee

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  1. Y. K. Liu
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  2. S. K. Ong
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Correspondence to S. K. Ong.

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Liu, Y.K., Ong, S.K. & Nee, A.Y.C. State-of-the-art survey on digital twin implementations. Adv. Manuf. 10, 1–23 (2022). https://doi.org/10.1007/s40436-021-00375-w

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  • DOI: https://doi.org/10.1007/s40436-021-00375-w

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