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A Manufacturability Evaluation of Complex Architectures by Laser Powder Bed Fusion Additive Manufacturing.

Authors :
McGregor, Martine
Patel, Sagar
Zhang, Kevin
Yu, Adam
Vlasea, Mihaela
McLachlin, Stewart
Source :
Journal of Manufacturing Science & Engineering. Jun2024, Vol. 146 Issue 6, p1-10. 10p.
Publication Year :
2024

Abstract

Additive manufacturing (AM) enables new possibilities for the design and manufacturing of complex metal architectures. Incorporating lattice structures into complex part geometries can enhance strength-to-weight and surface area-to-volume ratios for valuable components, particularly in industries such as medical devices and aerospace. However, lattice structures and their interconnections may result in unsupported down-skin surfaces, potentially limiting their manufacturability by metal AM technologies, such as laser powder bed fusion (LPBF). This study aimed to examine the correlation between down-skin surface area and the manufacturability of lattice structures fabricated using LPBF. Image processing algorithms were used to analyze down-skin surface areas of seven unique lattice designs and to devise quantitative metrics (such as down-skin surface area, discrete surface count, surface interconnectivity, down-skin ratio, over-print/under-print volumes, etc.) to evaluate LPBF manufacturability. The seven lattice designs were subsequently manufactured using maraging steel via LPBF and then examined using imaging using X-ray micro-computed tomography (XCT). The geometric accuracy of the lattice designs was compared with XCT scans of the manufactured lattices by employing a voxel-based image comparison technique. The results indicated a strong relationship between down-skin surface area, surface interconnectivity, and the manufacturability of a given lattice design. The digital manufacturability evaluation workflow was also applied to a medical device design, further affirming its potential industrial utility for complex geometries. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10871357
Volume :
146
Issue :
6
Database :
Academic Search Index
Journal :
Journal of Manufacturing Science & Engineering
Publication Type :
Academic Journal
Accession number :
177474298
Full Text :
https://doi.org/10.1115/1.4065315