Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/91421
PIRA download icon_1.1View/Download Full Text
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 (http://creativecommons.org/licenses/by-nc-nd/4.0)
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 https://doi.org/10.1016/j.procir.2021.05.031
Appears in Collections:Journal/Magazine Article

Files in This Item:
File Description SizeFormat 
1-s2.0-S2212827121004935-main.pdf795.72 kBAdobe PDFView/Open
Open Access Information
Status open access
File Version Version of Record
Access
View full-text via PolyU eLinks SFX Query
Show full item record

Page views

56
Last Week
0
Last month
Citations as of Mar 24, 2024

Downloads

22
Citations as of Mar 24, 2024

SCOPUSTM   
Citations

12
Citations as of Mar 28, 2024

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.