A Voxel-Based Design Approach for Creating Functionally Graded Structures via Material Extrusion Additive Manufacturing

Daniel R. Spillane, N. Meisel
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引用次数: 1

Abstract

Functionally graded materials (FGMs) are heterogeneous materials engineered to vary material composition across the volume of an object. Controlled mixture and deposition of each material through a manufactured part can ultimately allow for specific material properties defined in different regions of a structure. While such structures are traditionally difficult to manufacture, additive manufacturing processes, such as directed energy deposition, material jetting, and material extrusion, have recently increased the manufacturability of FGMs. However, the existing digital design workflow lacks the ability to accurately mix and assign multiple materials to a given volume, especially in the case of toolpath dependent deposition processes like filament-based material extrusion. In this paper, we will address this limitation by using a voxel-based representation approach, where material values are assigned across a pixel grid on each geometry slice before converting to toolpath information for manufacturing. This approach allows for creation of structures with increased material complexity decoupled from the external geometry of the design space, an approach not yet demonstrated in the existing literature. By using a dual-feed, single melt-pool extrusion nozzle system, this research demonstrates the ability to accurately recreate mathematically derived gradients while establishing a digital workflow capable of integrating with the material extrusion AM process.
基于体素的材料挤压增材制造功能梯度结构设计方法
功能梯度材料(fgm)是一种异质材料,可以在物体的体积范围内改变材料成分。通过制造部件控制每种材料的混合和沉积,最终可以在结构的不同区域定义特定的材料特性。虽然这种结构传统上很难制造,但最近,定向能沉积、材料喷射和材料挤压等增材制造工艺提高了fgm的可制造性。然而,现有的数字设计工作流程缺乏准确混合和分配多种材料到给定体积的能力,特别是在依赖于刀具轨迹的沉积工艺(如长丝基材料挤压)的情况下。在本文中,我们将通过使用基于体素的表示方法来解决这一限制,其中材料值在每个几何切片上的像素网格上分配,然后转换为制造的刀具路径信息。这种方法允许创建具有增加的材料复杂性的结构,与设计空间的外部几何解耦,这种方法尚未在现有文献中得到证明。通过使用双进料、单熔池挤出喷嘴系统,本研究证明了在建立能够与材料挤出AM工艺集成的数字工作流程的同时,能够准确地重建数学推导的梯度的能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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