Laser powder bed fusion for AI assisted digital metal components

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 assistan...

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Main Authors: Seo, Eunhyeok, Sung, Hyokyung, Jeon, Hongryoung, Kim, Hayeol, Kim, Taekyeong, Park, Sangeun, Lee, Min Sik, Moon, Seung Ki, Kim, Jung Gi, Chung, Hayoung, Choi, Seong-Kyum, Yu, Ji-Hun, Kim, Kyung Tae, Park, Seong Jin, Kim, Namhun, Jung, Im Doo
Other Authors: School of Mechanical and Aerospace Engineering
Format: Article
Language:English
Published: 2022
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Online Access:https://hdl.handle.net/10356/161513
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1615132022-09-06T05:29:18Z Laser powder bed fusion for AI assisted digital metal components Seo, Eunhyeok Sung, Hyokyung Jeon, Hongryoung Kim, Hayeol Kim, Taekyeong Park, Sangeun Lee, Min Sik Moon, Seung Ki Kim, Jung Gi Chung, Hayoung Choi, Seong-Kyum Yu, Ji-Hun Kim, Kyung Tae Park, Seong Jin Kim, Namhun Jung, Im Doo School of Mechanical and Aerospace Engineering Engineering::Mechanical engineering Laser Powder Bed Fusion Artificial Intelligence 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. This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) [grant Nos. 2021M2D2A1A01050059 and 2021R1F1A1046079]. 2022-09-06T05:29:18Z 2022-09-06T05:29:18Z 2022 Journal Article Seo, E., Sung, H., Jeon, H., Kim, H., Kim, T., Park, S., Lee, M. S., Moon, S. K., Kim, J. G., Chung, H., Choi, S., Yu, J., Kim, K. T., Park, S. J., Kim, N. & Jung, I. D. (2022). Laser powder bed fusion for AI assisted digital metal components. Virtual and Physical Prototyping, 17(4), 806-820. https://dx.doi.org/10.1080/17452759.2022.2068804 1745-2759 https://hdl.handle.net/10356/161513 10.1080/17452759.2022.2068804 2-s2.0-85132648133 4 17 806 820 en Virtual and Physical Prototyping © 2022 Informa UK Limited, trading as Taylor & Francis Group. All rights reserved.
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Mechanical engineering
Laser Powder Bed Fusion
Artificial Intelligence
spellingShingle Engineering::Mechanical engineering
Laser Powder Bed Fusion
Artificial Intelligence
Seo, Eunhyeok
Sung, Hyokyung
Jeon, Hongryoung
Kim, Hayeol
Kim, Taekyeong
Park, Sangeun
Lee, Min Sik
Moon, Seung Ki
Kim, Jung Gi
Chung, Hayoung
Choi, Seong-Kyum
Yu, Ji-Hun
Kim, Kyung Tae
Park, Seong Jin
Kim, Namhun
Jung, Im Doo
Laser powder bed fusion for AI assisted digital metal components
description 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.
author2 School of Mechanical and Aerospace Engineering
author_facet School of Mechanical and Aerospace Engineering
Seo, Eunhyeok
Sung, Hyokyung
Jeon, Hongryoung
Kim, Hayeol
Kim, Taekyeong
Park, Sangeun
Lee, Min Sik
Moon, Seung Ki
Kim, Jung Gi
Chung, Hayoung
Choi, Seong-Kyum
Yu, Ji-Hun
Kim, Kyung Tae
Park, Seong Jin
Kim, Namhun
Jung, Im Doo
format Article
author Seo, Eunhyeok
Sung, Hyokyung
Jeon, Hongryoung
Kim, Hayeol
Kim, Taekyeong
Park, Sangeun
Lee, Min Sik
Moon, Seung Ki
Kim, Jung Gi
Chung, Hayoung
Choi, Seong-Kyum
Yu, Ji-Hun
Kim, Kyung Tae
Park, Seong Jin
Kim, Namhun
Jung, Im Doo
author_sort Seo, Eunhyeok
title Laser powder bed fusion for AI assisted digital metal components
title_short Laser powder bed fusion for AI assisted digital metal components
title_full Laser powder bed fusion for AI assisted digital metal components
title_fullStr Laser powder bed fusion for AI assisted digital metal components
title_full_unstemmed Laser powder bed fusion for AI assisted digital metal components
title_sort laser powder bed fusion for ai assisted digital metal components
publishDate 2022
url https://hdl.handle.net/10356/161513
_version_ 1744365371334328320