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Constrained stacking in DLP 3D printing
Computers & Graphics ( IF 2.5 ) Pub Date : 2021-01-28 , DOI: 10.1016/j.cag.2021.01.003
Lingxin Cao , Lihao Tian , Hao Peng , Yu Zhou , Lin Lu

Using stacked models for 3D printing could significantly improve printing efficiency and save printing time. For standard 3D printing techniques like Fused Deposition Modeling (FDM) or Digital Light Processing (DLP), support structures are required for overhanging areas, even between the stacked models. However, there are requirements from medical applications like 3D printed dental implant guides, that support structures are not allowed to be placed on some restricted regions to maintain models’ appearance quality and accuracy. This paper introduces a constrained multi-level stacking scheme for DLP 3D printers, aiming to stack as many models as possible in the printing space; meanwhile, no support is placed on the restricted regions. We rotate each stacked model along the axis and calculate the feasible pose set that restricted regions have no overhanging surface. We further propose a level-based scaffold structure to arrange the stacked models level by level. Therefore, support structures could be generated on the scaffold, and the stacked model does not need to support each other. We employ a heuristic strategy for each level to iteratively select a candidate model and its posture to achieve a locally optimal arrangement. We then introduce perturbations in the arrangement order, using a hill-climbing method to approximate the most volume-efficient arrangement.



中文翻译:

DLP 3D打印中的堆叠受限

使用堆叠模型进行3D打印可以显着提高打印效率并节省打印时间。对于诸如熔融沉积建模(FDM)或数字光处理(DLP)之类的标准3D打印技术,即使在堆叠的模型之间,也需要用于悬垂区域的支撑结构。但是,医疗应用(例如3D打印的牙科植入物导向器)有一些要求,即不允许将支撑结构放置在某些受限区域上,以保持模型的外观质量和准确性。本文介绍了一种用于DLP 3D打印机的受约束的多层堆叠方案,旨在在打印空间中堆叠尽可能多的模型。同时,禁区没有任何支持。我们沿着轴旋转每个堆叠模型,并计算出可行的姿势集,即受限区域没有悬垂表面。我们进一步提出了一个基于级别的脚手架结构,以逐级排列堆叠的模型。因此,可以在支架上产生支撑结构,并且堆叠的模型不需要彼此支撑。我们为每个级别采用启发式策略,以迭代方式选择候选模型及其姿态以实现局部最优布置。然后,我们使用爬山方法按排列顺序引入扰动,以近似最节省体积的排列。并且堆叠模型不需要相互支持。我们为每个级别采用启发式策略,以迭代方式选择候选模型及其姿态以实现局部最优布置。然后,我们使用爬山方法按排列顺序引入扰动,以近似最节省体积的排列。并且堆叠模型不需要相互支持。我们为每个级别采用启发式策略,以迭代方式选择候选模型及其姿态以实现局部最优布置。然后,我们使用爬山方法按排列顺序引入扰动,以近似最节省体积的排列。

更新日期:2021-02-12
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