Development and Experimental Study of an Automated Laser-Foil-Printing Additive Manufacturing System
Abstract
Purpose: This paper aims to present the development and experimental study of a fully automated system using a novel laser additive manufacturing technology called laser foil printing (LFP), to fabricate metal parts layer by layer. The mechanical properties of parts fabricated with this novel system are compared with those of comparable methodologies to emphasize the suitability of this process.
Design/methodology/approach: Test specimens and parts with different geometries were fabricated from 304L stainless steel foil using an automated LFP system. The dimensions of the fabricated parts were measured, and the mechanical properties of the test specimens were characterized in terms of mechanical strength and elongation.
Findings: The properties of parts fabricated with the automated LFP system were compared with those of parts fabricated with the powder bed fusion additive manufacturing methods. The mechanical strength is higher than those of parts fabricated by the laser powder bed fusion and directed energy deposition technologies.
Originality/value: To the best knowledge of authors, this is the first time a fully automated LFP system has been developed and the properties of its fabricated parts were compared with other additive manufacturing methods for evaluation.
Recommended Citation
C. H. Hung et al., "Development and Experimental Study of an Automated Laser-Foil-Printing Additive Manufacturing System," Rapid Prototyping Journal, Emerald, Jan 2022.
The definitive version is available at https://doi.org/10.1108/RPJ-10-2021-0269
Department(s)
Mechanical and Aerospace Engineering
Research Center/Lab(s)
Intelligent Systems Center
Keywords and Phrases
304L Stainless Steel; Additive Manufacturing; Laser-Based Manufacturing; Metal Foil; Sheet Metal Lamination
International Standard Serial Number (ISSN)
1355-2546
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2022 Emerald, All rights reserved.
Publication Date
12 Jan 2022
Comments
This research work was supported by the Department of Energy (Grant number DE-FE0012272) and by the Intelligent Systems Center at the Missouri University of Science and Technology.