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Laser powder bed fusion for AI assisted digital metal components

Authors :
Eunhyeok Seo
Hyokyung Sung
Hongryoung Jeon
Hayeol Kim
Taekyeong Kim
Sangeun Park
Min Sik Lee
Seung Ki Moon
Jung Gi Kim
Hayoung Chung
Seong-Kyum Choi
Ji-Hun Yu
Kyung Tae Kim
Seong Jin Park
Namhun Kim
Im Doo Jung
Source :
Virtual and Physical Prototyping, Vol 17, Iss 4, Pp 806-820 (2022)
Publication Year :
2022
Publisher :
Taylor & Francis Group, 2022.

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.

Details

Language :
English
ISSN :
17452759 and 17452767
Volume :
17
Issue :
4
Database :
Directory of Open Access Journals
Journal :
Virtual and Physical Prototyping
Publication Type :
Academic Journal
Accession number :
edsdoj.2c3cfe3449374b00ae9bf52cccc7b305
Document Type :
article
Full Text :
https://doi.org/10.1080/17452759.2022.2068804