AI 中文总结
针对异构制造中设计意图难以重用问题，提出将设计视为分阶段、类型化降阶问题的编译器架构，通过翻译模型和后端编译器实现不同表示形式转换，经实验验证有效并开源相关内容加速研究。
AI 中文摘要
计算制造工作流程日益要求设计师指定空间变化的行为、外观、材料成分和工艺状态。但多数工作流程将这些意图强制转换为特定打印机的表示形式，导致异构设计难以重用。本文提出一种异构制造编译器架构，将设计视为分阶段、类型化的降阶问题。源设计由隐式几何和共享对象域上命名、类型化的空间属性字段组成。翻译模型从源或意图属性派生编译器所需的实现属性，后端编译器生成面向机器的输出。通过制造对象和测量验证了该方法，结果表明一个源设计可转换为不同表示形式，且以开源Python包提供相关内容以加速异构计算制造研究。
英文摘要
Computational fabrication workflows increasingly require designers to specify spatially varying behavior, appearance, material composition, and process state. Yet most workflows force these intentions into printer-specific representations, such as material fractions, voxel labels, mesh partitions, or slicer settings. This coupling makes heterogeneous designs difficult to reuse because each backend requires a different realization of the same property. We present a compiler architecture for heterogeneous fabrication that treats design as a staged, typed lowering problem. A source design consists of implicit geometry and named, typed spatial attribute fields over a shared object domain. These attributes may encode measured data, visual appearance, target mechanical behavior, material recipes, process parameters, or other user-specified attributes. Translation models derive compiler-required realization attributes from source or intent attributes, and backend compilers emit machine-facing outputs such as voxel material stacks, process G-code, or configured slicer project files. This separates source modeling, attribute translation, and backend compilation, allowing a design to remain expressed in fabrication-agnostic terms while each toolchain determines how intent becomes executable instructions. We validate the method through fabricated objects and measurements across sampled volumetric data, CT-derived visual and mechanical models, Shore-hardness fields, and full-color fields, implemented via material jetting and material extrusion. These results show that one source design can be lowered into distinct material, process, and slicer representations without rewriting it in printer-specific terms. We provide the representation, translation framework, compiler interface, and workflows as an open-source Python package to accelerate research in heterogeneous computational fabrication.
Comments21 pages, 12 figures, supplementary material
