This paper presents a robust algorithm to generate support for fused deposition modeling (FDM). Since many flaws appear in most stereo lithography (STL) models, this algorithm utilizes slice data as input. A top-down ...This paper presents a robust algorithm to generate support for fused deposition modeling (FDM). Since many flaws appear in most stereo lithography (STL) models, this algorithm utilizes slice data as input. A top-down approach was used to calculate the support slice layer by layer. The generation algorithm was described in detail including the slice grouping, oriental bounding box (OBB) calculation, offsetting, and Boolean operations. Several cases are given to validate the efficiency and robustness of the procedure. The algorithm provides necessary support not only for hanging surface but also for hanging vertexes and edges with O(n) time complexity, where n is the number of layers. The algorithm fully utilizes the parts’ self-support ability and reduces support volume to the maximum extent. This slice data based algorithm has the same efficiency as the STL based algorithm but is more stable, which significantly enhances the robustness of the support generation process.展开更多
基金Supported by the Natural Science Fund Project of Hubei Province of China (2004ABC001)
文摘This paper presents a robust algorithm to generate support for fused deposition modeling (FDM). Since many flaws appear in most stereo lithography (STL) models, this algorithm utilizes slice data as input. A top-down approach was used to calculate the support slice layer by layer. The generation algorithm was described in detail including the slice grouping, oriental bounding box (OBB) calculation, offsetting, and Boolean operations. Several cases are given to validate the efficiency and robustness of the procedure. The algorithm provides necessary support not only for hanging surface but also for hanging vertexes and edges with O(n) time complexity, where n is the number of layers. The algorithm fully utilizes the parts’ self-support ability and reduces support volume to the maximum extent. This slice data based algorithm has the same efficiency as the STL based algorithm but is more stable, which significantly enhances the robustness of the support generation process.
