Laser powder bed fusion for AI assisted digital metal components. Issue 4 (2nd October 2022)

• Record Type: Journal Article
• 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
• Is Part Of: Virtual and physical prototyping. Volume 17:Issue 4(2022)
• Page Start: 806
• Page End: 820
• Publication Date: 2022-10-02
• Subjects: Laser powder bed fusion -- artificial intelligence -- sensor embedding -- digital metal component -- augmented reality; Rapid prototyping -- Periodicals; Virtual computer systems -- Periodicals; Prototypes, Engineering -- Periodicals; Production engineering -- Periodicals; Design, Industrial -- Periodicals; 670.285
• DOI: 10.1080/17452759.2022.2068804
• Languages: English
• ISSNs: 1745-2759

Abstract

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.