Edge-Enhanced Object-Space Model Optimization of Tomographic Reconstructions for Additive Manufacturing

Object-space model optimization (OSMO) has been proven to be a simple and high-accuracy approach for additive manufacturing of tomographic reconstructions compared with other approaches. In this paper, an improved OSMO algorithm is proposed in the context of OSMO. In addition to the two model optimi...

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Bibliographic Details
Published in:Micromachines (Basel) 2023-06, Vol.14 (7), p.1362
Main Authors: Zhang, Yanchao, Liu, Minzhe, Liu, Hua, Gao, Ce, Jia, Zhongqing, Zhai, Ruizhan
Format: Article
Language:English
Subjects:
3D printing
Accuracy
Additive manufacturing
Algorithms
Comparative analysis
edge enhanced
Geometry
Iterative methods
Manufacturing
Morphology
Optimization
OSMO
tomographic reconstruction
Tomography
volumetric additive manufacturing
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Summary:Object-space model optimization (OSMO) has been proven to be a simple and high-accuracy approach for additive manufacturing of tomographic reconstructions compared with other approaches. In this paper, an improved OSMO algorithm is proposed in the context of OSMO. In addition to the two model optimization steps in each iteration of OSMO, another two steps are introduced: one step enhances the target regions' in-part edges of the intermediate model, and the other step weakens the target regions' out-of-part edges of the intermediate model to further improve the reconstruction accuracy of the target boundary. Accordingly, a new quality metric for volumetric printing, named 'Edge Error', is defined. Finally, reconstructions on diverse exemplary geometries show that all the quality metrics, such as VER, PW, IPDR, and Edge Error, of the new algorithm are significantly improved; thus, this improved OSMO approach achieves better performance in convergence and accuracy compared with OSMO.
ISSN:2072-666X
2072-666X
DOI:10.3390/mi14071362