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Cited 4 time in webofscience Cited 4 time in scopus
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Laser powder bed fusion for AI assisted digital metal components

Authors
Seo, EunhyeokSung, HyokyungJeon, HongryoungKim, HayeolKim, TaekyeongPark, SangeunLee, Min SikMoon, Seung KiKim, Jung GiChung, HayoungChoi, Seong-KyumYu, Ji-HunKim, Kyung TaePark, Seong JinKim, NamhunJung, Im Doo
Issue Date
Oct-2022
Publisher
Taylor & Francis
Keywords
Laser powder bed fusion; artificial intelligence; sensor embedding; digital metal component; augmented reality
Citation
Virtual and Physical Prototyping, v.17, no.4, pp 806 - 820
Pages
15
Indexed
SCIE
SCOPUS
Journal Title
Virtual and Physical Prototyping
Volume
17
Number
4
Start Page
806
End Page
820
URI
https://scholarworks.gnu.ac.kr/handle/sw.gnu/71646
DOI
10.1080/17452759.2022.2068804
ISSN
1745-2759
1745-2767
Abstract
This paper proposes a novel method to impart intelligence to metal parts using additive manufacturing. A sensor-embedded metal bracket is prototyped via a metal powder bed fusion process to recognise partial screw loosening or total screw missing or identify the source of vibration with the assistance of artificial intelligence (AI). The digital metal bracket can recognise subtle changes in the screw fixation state with 90% accuracy and identify unknown sources of vibration with 84% accuracy. The von Mises stress distribution in the prototyped metal bracket is evaluated using a finite element analysis, which is learned by AI to match the real-time deformation analysis of the metal bracket in augmented reality. The proposed prototype can contribute to hyper-connectivity for developing next-generation metal-based mechanical components.
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공학계열 > Dept.of Materials Engineering and Convergence Technology > Journal Articles

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Kim, Jung Gi
대학원 (나노신소재융합공학과)
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