Prediction of 3D Printing Bottom Plate Amount Using Open Source Software and Support Structure Tomography 


Vol. 60,  No. 4, pp. 249-255, Aug.  2023
10.12772/TSE.2023.60.249


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  Abstract

The purpose of this study is to present a modified calculation scheme, designated as support structure tomography, which can easily predict and minimize the amount of the support structure in human mannequin 3D printing. It started with voxelization of triangular mannequin mesh and predicted the information of support structure by triangles’ normal vector information. However, it did not consider the bottom plate options although they are critical factors in 3D printing. This work proposes a modified algorithm that can predict both the support structure and the bottom structure using open-source software, so that non-professional users can easily adopt it to their own uses. The proposed algorithm’s accuracy was compared with that of g-code-based slicing software for the Stanford Bunny data.

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  Cite this article

[IEEE Style]

J. Y. Jung and I. H. Sul, "Prediction of 3D Printing Bottom Plate Amount Using Open Source Software and Support Structure Tomography," Textile Science and Engineering, vol. 60, no. 4, pp. 249-255, 2023. DOI: 10.12772/TSE.2023.60.249.

[ACM Style]

Jin Young Jung and In Hwan Sul. 2023. Prediction of 3D Printing Bottom Plate Amount Using Open Source Software and Support Structure Tomography. Textile Science and Engineering, 60, 4, (2023), 249-255. DOI: 10.12772/TSE.2023.60.249.

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pISSN : 1225 - 1089
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한국연구재단 우수등재학술지 유지 (2022년)