Abstract
In fused filament fabrication (FFF), the orientation of a part within the printer volume can dramatically affect print quality and probability of success. An object's orientation determines how much support structure will be required and the strength of adhesion between the deposited material and the build surface. Selecting a part's orientation is a non-trivial problem that users of FFF slicing software face routinely. Numerous part orientations need to be considered to find the best according to the results of the slicing process. This paper presents a method to automatically determine an optimal printing orientation for FFF that maximizes build-surface adhesion while minimizing the need for support structure. The algorithm considers the slicing angle and a configurable angle for overhang that requires supporting structure. By employing GPU acceleration and convex hull analysis to limit candidate orientations, the algorithm can run in real time as a preprocessing aid to users slicing parts.
Original language | English |
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Title of host publication | Proceedings - SCF 2023 |
Subtitle of host publication | 8th Annual ACM Symposium on Computational Fabrication |
Editors | Stephen N. Spencer |
Publisher | Association for Computing Machinery, Inc |
ISBN (Electronic) | 9798400703195 |
DOIs | |
State | Published - Oct 8 2023 |
Event | 8th Annual ACM Symposium on Computational Fabrication, SCF 2023 - New York, United States Duration: Oct 8 2023 → Oct 10 2023 |
Publication series
Name | Proceedings - SCF 2023: 8th Annual ACM Symposium on Computational Fabrication |
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Conference
Conference | 8th Annual ACM Symposium on Computational Fabrication, SCF 2023 |
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Country/Territory | United States |
City | New York |
Period | 10/8/23 → 10/10/23 |
Funding
This material is based upon work supported by the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Office of Advanced Manufacturing, under contract number DE-AC05-00OR22725. This work is described in US patent application, Serial Number 16/842,274 (filed on April 7, 2020.)
Keywords
- GPU acceleration
- additive manufacturing
- computer-aided design
- optimization
- toolpath-planning