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Title: Artificial intelligence enhanced interaction in digital twin shop-floor
Authors: Ma, X
Cheng, J
Qi, Q 
Tao, F
Issue Date: 2021
Source: Procedia CIRP, 2021, v. 100, p. 858-863
Abstract: As an enabling technology for smart manufacturing, digital twin has been widely applied in manufacturing shop-floor. A great deal of research focuses on the key issues in implementing digital twin shop-floor (DTS), including scheduling, production planning, fault diagnosis and prognostics. However, DTS puts forward higher requirements in terms of real-time interaction. Artificial intelligence (AI), as an effective approach to improve the intelligence of the physical shop-floor, provides a new method to meet the above requirements. In this paper, a framework of AI-enhanced DTS in interaction is proposed. AI-enhanced DTS improves the real-time interaction through predictive control. The implementation mechanism of AI-enhanced interaction in DTS is also presented in detail. Enabling technologies for interaction in DTS are introduced at last.
Keywords: Artificial intelligence (AI)
Digital twin shop-floor (DTS)
Real-time interaction
Publisher: Elsevier
Journal: Procedia CIRP 
ISSN: 2212-8271
DOI: 10.1016/j.procir.2021.05.031
Rights: © 2021 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (
The following publication Ma, X., Cheng, J., Qi, Q., & Tao, F. (2021). Artificial intelligence enhanced interaction in digital twin shop-floor. Procedia CIRP, 100, 858-863 is available at
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