Manufacturing automation in process planning, inspection planning, and digital-thread integration depends on a unified specification that binds the geometric features of a 3D CAD model to the geometric dimensioning and tolerancing (GD&T) callouts, datum definitions, and surface requirements carried by the corresponding 2D engineering drawing. Although Model-Based Definition (MBD) allows such specifications to be embedded directly in 3D models, 2D drawings remain the primary carrier of manufacturing intent in automotive, aerospace, shipbuilding, and heavy-machinery industries. Correctly linking drawing annotations to the corresponding 3D features is difficult because of contextual ambiguity, repeated feature patterns, and the need for transparent and traceable decisions. This paper presents a deterministic-first, context-aware framework that maps 2D drawing entities to 3D CAD features to produce a unified manufacturing specification. Drawing callouts are first semantically enriched and then scored against candidate features using an interpretable metric that combines type compatibility, tolerance-aware dimensional agreement, and conservative context consistency, along with engineering-domain heuristics. When deterministic scoring cannot resolve an ambiguity, the system escalates to multimodal and constrained large-language-model reasoning, followed by a single human-in-the-loop (HITL) review step. Experiments on 20 real CAD-drawing pairs achieve a mean precision of 83.67%, recall of 90.46%, and F1 score of 86.29%. An ablation study shows that each pipeline component contributes to overall accuracy, with the full system outperforming all reduced variants. By prioritizing deterministic rules, clear decision tracking, and retaining unresolved cases for human review, the framework provides a practical foundation for downstream manufacturing automation in real-world industrial environments.

翻译：在工艺规划、检测规划与数字主线集成等制造自动化环节中，统一的规范至关重要，它需要将三维CAD模型的几何特征与对应二维工程图所承载的几何尺寸与公差标注、基准定义及表面要求进行绑定。尽管基于模型的定义允许此类规范直接嵌入三维模型，但在汽车、航空航天、造船及重型机械等行业，二维图纸仍是制造意图的主要载体。由于上下文歧义、重复特征模式以及对决策透明性与可追溯性的要求，将图纸标注正确关联至对应的三维特征十分困难。本文提出一种确定性优先、上下文感知的框架，通过将二维图纸实体映射至三维CAD特征来生成统一的制造规范。该框架首先对图纸标注进行语义增强，随后采用一种可解释的度量方法对候选特征进行评分，该度量综合了类型兼容性、公差感知的尺寸一致性、保守的上下文一致性以及工程领域启发式规则。当确定性评分无法解决歧义时，系统将升级至多模态与受约束的大语言模型推理，并随后执行单次人在回路审查步骤。在20组真实CAD-图纸对上进行的实验取得了平均精确率83.67%、召回率90.46%及F1分数86.29%的结果。消融研究表明，流程中的每个组件都对整体准确性有所贡献，完整系统的性能优于所有简化变体。通过优先采用确定性规则、保持清晰的决策追踪并将未决案例交由人工审查，该框架为现实工业环境中的下游制造自动化提供了实用基础。