Guo, Q., Ye, J. orcid.org/0000-0002-6857-7450, Lu, H. et al. (4 more authors) (2024) Design and validation of 3D self-supporting structures and printing paths for multi-axis additive manufacturing. Additive Manufacturing, 96. 104563. ISSN 2214-8604
Abstract
Additive manufacturing (AM) has become a widely used tool for fabricating components with complex geometries. However, the overhang effect induced by gravity often necessitates additional supports to prevent collapse and warping during the printing process. To address this issue, previous studies incorporated overhang constraints to the topology optimisation to create self-supporting structures. Nevertheless, these studies primarily focused on 3-axis AM, which deposits material in a single direction and often compromises structural stiffness to achieve self-supporting designs. In response, this study aims to design 3D self-supporting structures tailored for multi-axis AM. By leveraging the rotatable base platform of multi-axis systems, this approach automatically identifies optimised local build directions and the corresponding structural topology to minimise overhangs. The effectiveness of this approach is demonstrated through several numerical examples, with results validated numerically via printing simulations in VERICUT and physically using a multi-axis Wire Arc Additive Manufacturing (WAAM) machine. The results indicate that the performance degradation caused by 3-axis-based overhang constraints can be reduced to a negligible level with the multi-axis-based approach.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2024 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by- nc-nd/4.0/). |
Keywords: | Topology optimisation; Overhang constraint; Multi-axis AM; Self-supporting structure |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > SWJTU Joint School (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 22 Jan 2025 10:20 |
Last Modified: | 22 Jan 2025 10:20 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.addma.2024.104563 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:222071 |