HistCAD: Geometrically Constrained Parametric History-based CAD Dataset

2025-12-08

arXiv.org

AI Summary

Existing CAD generation datasets lack the capability to evaluate design intent preservation—specifically, constraint consistency—after parametric edits. This work proposes HistCAD, a CAD-software-agnostic intermediate language that explicitly encodes sketch primitives, geometric and dimensional constraints, feature operations, and 3D boundary references within sequential representations. Leveraging this representation, we construct a dataset of 170,000 executable sequences and establish a new benchmark focused on editability. We introduce three metrics—Edit Reachability (ER), constraint-preserving command sequence ratio (cPCSR), and operation edit similarity (OES)—to distinguish between edit accessibility and constraint preservation. Experiments demonstrate that explicit constraint modeling is crucial for maintaining design intent. HistCAD enables both text-supervised generation and end-to-end CAD synthesis with large language models, validated on industrial-scale complex models, thereby advancing CAD generation from static shape imitation toward reusable, parameterized sequence synthesis.

Abstract

Parametric computer-aided design (CAD) modeling is fundamental to industrial design, but existing datasets often lack explicit geometric constraints and fine-grained functional semantics, limiting editable, constraint-compliant generation. We present HistCAD, a large-scale dataset featuring constraint-aware modeling sequences that compactly represent procedural operations while ensuring compatibility with native CAD software, encompassing five aligned modalities: modeling sequences, multi-view renderings, STEP-format B-reps, native parametric files, and textual annotations. We develop AM\(_\text{HistCAD}\), an annotation module that extracts geometric and spatial features from modeling sequences and uses a large language model to generate complementary annotations of the modeling process, geometric structure, and functional type. Extensive evaluations demonstrate that HistCAD's explicit constraints, flattened sequence format, and multi-type annotations improve robustness, parametric editability, and accuracy in text-driven CAD generation, while industrial parts included in HistCAD further support complex real-world design scenarios. HistCAD thus provides a unified benchmark for advancing editable, constraint-aware, and semantically enriched generative CAD modeling.

Problem

• parametric CAD
• design intent
• geometric constraints
• editability
• constraint preservation

Innovation

• parametric CAD
• design intent preservation
• constraint-aware representation
• executable CAD sequences
• CAD benchmarking