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Cited 2 time in webofscience Cited 2 time in scopus
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Laser powder bed fusion for AI assisted digital metal components SCIE SCOPUS

Title
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
Date Issued
2022-10
Publisher
TAYLOR & FRANCIS LTD
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.
URI
https://oasis.postech.ac.kr/handle/2014.oak/113010
DOI
10.1080/17452759.2022.2068804
ISSN
1745-2759
Article Type
Article
Citation
VIRTUAL AND PHYSICAL PROTOTYPING, vol. 17, no. 4, page. 806 - 820, 2022-10
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박성진PARK, SEONG JIN
Dept of Mechanical Enginrg
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