2019
DOI: 10.3390/app9183868
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A G-Code Generator for Volumetric Models

Abstract: In layered manufacturing (LM), slicers are employed to convert input geometric models into G-codes. Conventional slicers accept only surface models as input data. Thus, volumetric models have to be converted into polygonal representations to fit the data format of the slicers. This results in extra computational costs and geometric errors. In this article, we present an efficient slicer aiming to generate G-codes for volumetric models. At first, our slicer computes the printing direction by exploring the inert… Show more

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Cited by 1 publication
(2 citation statements)
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“…The former is responsible for embedding watermarks, while the latter is utilized to verify contents. Besides these two programs, the slicer and simulator, developed in the researches of [26] and [27], are also employed to translate voxel models into G-code programs and to convert G-code programs into voxel models, respectively. Many experiments had been designed and conducted to test the system.…”
Section: Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…The former is responsible for embedding watermarks, while the latter is utilized to verify contents. Besides these two programs, the slicer and simulator, developed in the researches of [26] and [27], are also employed to translate voxel models into G-code programs and to convert G-code programs into voxel models, respectively. Many experiments had been designed and conducted to test the system.…”
Section: Resultsmentioning
confidence: 99%
“…This slicer is capable of translating voxel models into G-code programs. Its algorithms, data structures, and operational procedures can be found in [26]. During the G-code generation procedure, the space occupied by watermarked voxels is treated as void spaces or filled with different hatch patterns or materials, depending on the characteristics of the underlying 3D-printing platforms and the applications of the model.…”
Section: G-code and Physical Part Watermarkingmentioning
confidence: 99%