[2602.18296] Context-Aware Mapping of 2D Drawing Annotations to 3D CAD Features Using LLM-Assisted Reasoning for Manufacturing Automation

[2602.18296] Context-Aware Mapping of 2D Drawing Annotations to 3D CAD Features Using LLM-Assisted Reasoning for Manufacturing Automation

arXiv - AI 4 min read Article

Summary

This article presents a framework for mapping 2D drawing annotations to 3D CAD features using context-aware reasoning, enhancing manufacturing automation accuracy.

Why It Matters

The ability to accurately link 2D annotations to 3D CAD features is crucial for manufacturing sectors like automotive and aerospace, where precision impacts efficiency and quality. This framework addresses common challenges in the mapping process, potentially streamlining workflows and reducing errors in manufacturing automation.

Key Takeaways

  • Introduces a deterministic-first framework for mapping 2D to 3D CAD features.
  • Achieves high precision (83.67%) and recall (90.46%) in experiments with real CAD-drawing pairs.
  • Combines semantic enrichment and interpretable metrics for effective feature mapping.
  • Utilizes human-in-the-loop review for unresolved ambiguities, enhancing decision transparency.
  • Offers a practical solution for real-world manufacturing automation challenges.

Computer Science > Computational Engineering, Finance, and Science arXiv:2602.18296 (cs) [Submitted on 20 Feb 2026] Title:Context-Aware Mapping of 2D Drawing Annotations to 3D CAD Features Using LLM-Assisted Reasoning for Manufacturing Automation Authors:Muhammad Tayyab Khana, Lequn Chen, Wenhe Feng, Seung Ki Moon View a PDF of the paper titled Context-Aware Mapping of 2D Drawing Annotations to 3D CAD Features Using LLM-Assisted Reasoning for Manufacturing Automation, by Muhammad Tayyab Khana and 3 other authors View PDF HTML (experimental) Abstract: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 specifica...

Related Articles

Llms

What does Gemini think of you?

I noticed that Gemini was referring back to a lot of queries I've made in the past and was using that knowledge to drive follow up prompt...

Reddit - Artificial Intelligence · 1 min ·
Llms

This app helps you see what LLMs you can run on your hardware

submitted by /u/dev_is_active [link] [comments]

Reddit - Artificial Intelligence · 1 min ·
Llms

TRACER: Learn-to-Defer for LLM Classification with Formal Teacher-Agreement Guarantees

I'm releasing TRACER (Trace-Based Adaptive Cost-Efficient Routing), a library for learning cost-efficient routing policies from LLM trace...

Reddit - Machine Learning · 1 min ·
Mistral AI raises $830M in debt to set up a data center near Paris | TechCrunch
Llms

Mistral AI raises $830M in debt to set up a data center near Paris | TechCrunch

Mistral aims to start operating the data center by the second quarter of 2026.

TechCrunch - AI · 4 min ·
More in Llms: This Week Guide Trending

No comments

No comments yet. Be the first to comment!

Stay updated with AI News

Get the latest news, tools, and insights delivered to your inbox.

Daily or weekly digest • Unsubscribe anytime