通过将设计意图编译到切片器项目中对切片过程进行功能分级
Functionally Grading the Slicing Process by Compiling Design Intent into Slicer Projects
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中文总结 AI 辅助
研究如何对切片过程进行功能分级，核心方法是提出切片器项目编译的自动化工作流程，将异构隐式设计转换为切片器原生项目，主要贡献是通过示例展示该方法并开源实现，连接异构设计与切片器生态系统，助力功能分级FFF制造。
中文摘要 AI 辅助
功能梯度通过改变物体的结构、材料或工艺条件来控制部件行为。然而，功能分级制造通常被视为对几何形状或材料分布进行分级，而非切片和制造过程本身。在材料挤出打印中，许多功能效果源于切片器控制的机制。主流的熔融沉积成型（FFF）切片器将这些机制作为设置公开，但用户必须手动将异构意图重建为指定的网格区域。我们提出了切片器项目编译，这是一种自动化工作流程，可将异构隐式设计转换为包含子网格、设置、配方和过程状态分配的切片器原生.3MF项目。编译器将空间属性划分为有限区域，提取对齐的子网格，并将它们序列化到目标切片器的项目方言中，同时保留原生刀具路径规划、预览、支撑生成和打印机配置文件。我们在三个参数类别中展示了该方法：设置网格、虚拟挤出以及颜色或材料半色调。我们还为温度响应发泡TPU和PLA引入了校准翻译模型，允许高级密度和邵氏硬度场驱动可用于制造的过程场。打印示例包括分级刀具路径设置、发泡丝特性、纹理和过程状态的组合控制以及颜色或材料混合半色调，取代了超过2500次重复的手动切片器交互。我们的开源实现将异构设计表示与现有的切片器生态系统连接起来，并为自动化、可扩展的功能分级FFF制造提供了可重用的基础。
英文摘要
Functional gradients control part behavior by varying structure, material, or process conditions across an object. Yet functionally graded fabrication is usually framed as grading geometry or material distribution rather than the slicing and fabrication process itself. In material-extrusion printing, many functional effects arise from slicer-controlled mechanisms, including local toolpath planning, surface treatment, material assignment, color mixing, and printer state. Mainstream FFF slicers expose these mechanisms as settings, but users must manually reconstruct heterogeneous intent as assigned mesh regions. We present slicer project compilation, an automated workflow that lowers heterogeneous implicit designs into slicer-native .3MF projects containing sub-meshes, settings, recipes, and process-state assignments. The compiler partitions spatial attributes into finite regions, extracts aligned sub-meshes, and serializes them into the target slicer's project dialect while preserving native toolpath planning, preview, support generation, and printer profiles. We demonstrate the approach across three parameter classes: settings meshes, virtual extrusion, and color or material halftoning. We also introduce calibrated translation models for temperature-responsive foaming TPU and PLA, allowing high-level density and Shore-hardness fields to drive fabrication-ready process fields. Printed examples include graded toolpath settings, foaming-filament properties, combined texture and process-state control, and color or material-mixture halftoning, replacing more than 2,500 repetitive manual slicer interactions. Our open-source implementation connects heterogeneous design representations to existing slicer ecosystems and provides a reusable foundation for automated, scalable functionally graded FFF fabrication.
