Determining Optimal Print Orientation Using GPU-Accelerated Convex Hull Analysis

Charles Wade, Breanne Crockett, Michael Borish, Robert MacCurdy

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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 languageEnglish
Title of host publicationProceedings - SCF 2023
Subtitle of host publication8th Annual ACM Symposium on Computational Fabrication
EditorsStephen N. Spencer
PublisherAssociation for Computing Machinery, Inc
ISBN (Electronic)9798400703195
DOIs
StatePublished - Oct 8 2023
Event8th Annual ACM Symposium on Computational Fabrication, SCF 2023 - New York, United States
Duration: Oct 8 2023Oct 10 2023

Publication series

NameProceedings - SCF 2023: 8th Annual ACM Symposium on Computational Fabrication

Conference

Conference8th Annual ACM Symposium on Computational Fabrication, SCF 2023
Country/TerritoryUnited States
CityNew York
Period10/8/2310/10/23

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

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