提出双向中间表示Textile IR,打通服装设计全流程
Textile IR: A Bidirectional Intermediate Representation for Physics-Aware Fashion CAD
- 构建七层验证阶梯,实现制造、仿真与可持续性联动
- 支持实时反馈:仿真失败自动建议修改,材料替换即时更新碳排
- 适合关注可持续设计的服装企业与AI辅助设计研究者
我们提出Textile IR,一种双向中间表示,连接可制造的CAD、物理仿真与生命周期评估,用于时尚设计。不同于传统工具中图案软件仅保证可缝制但忽略垂感,或物理仿真能预测行为却无法自动修正图案的问题,Textile IR通过七层验证阶梯(从廉价的语法检查到昂贵的物理验证)提供语义整合。该架构支持双向反馈:仿真失败提示图案调整;材料替换实时更新可持续性评估;不确定性在流程中传递并附带显式置信区间。我们将时尚工程形式化为三领域约束满足问题,并证明其场景图表示使AI系统能将服装视为结构化程序而非像素阵列。针对测量误差、仿真近似与LCA数据库缺口叠加导致的可靠性问题,框架引入显式不确定性追踪。提出六项研究方向,讨论中小型企业部署考量,集成工作流可降低专业工程需求。核心贡献是使工程约束可见、可操作且即时影响决策,让设计师同步权衡可持续性、可制造性与美学,而非在昂贵实物原型后才发现冲突。
原文摘要 · Abstract (English)
We introduce Textile IR, a bidirectional intermediate representation that connects manufacturing-valid CAD, physics-based simulation, and lifecycle assessment for fashion design. Unlike existing siloed tools where pattern software guarantees sewable outputs but understands nothing about drape, and physics simulation predicts behaviour but cannot automatically fix patterns, Textile IR provides the semantic glue for integration through a seven-layer Verification Ladder -- from cheap syntactic checks (pattern closure, seam compatibility) to expensive physics validation (drape simulation, stress analysis). The architecture enables bidirectional feedback: simulation failures suggest pattern modifications; material substitutions update sustainability estimates in real time; uncertainty propagates across the pipeline with explicit confidence bounds. We formalise fashion engineering as constraint satisfaction over three domains and demonstrate how Textile IR's scene-graph representation enables AI systems to manipulate garments as structured programs rather than pixel arrays. The framework addresses the compound uncertainty problem: when measurement errors in material testing, simulation approximations, and LCA database gaps combine, sustainability claims become unreliable without explicit uncertainty tracking. We propose six research priorities and discuss deployment considerations for fashion SMEs where integrated workflows reduce specialised engineering requirements. Key contribution: a formal representation that makes engineering constraints perceptible, manipulable, and immediately consequential -- enabling designers to navigate sustainability, manufacturability, and aesthetic tradeoffs simultaneously rather than discovering conflicts after costly physical prototyping.
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