Generative AI for CAD Automation: Leveraging Large Language Models for 3D Modelling
July 05, 2025 Β· Declared Dead Β· π arXiv.org
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Authors
Sumit Kumar, Sarthak Kapoor, Harsh Vardhan, Yao Zhao
arXiv ID
2508.00843
Category
cs.HC: Human-Computer Interaction
Cross-listed
cs.AI,
cs.SE
Citations
2
Venue
arXiv.org
Last Checked
4 months ago
Abstract
Large Language Models (LLMs) are revolutionizing industries by enhancing efficiency, scalability, and innovation. This paper investigates the potential of LLMs in automating Computer-Aided Design (CAD) workflows, by integrating FreeCAD with LLM as CAD design tool. Traditional CAD processes are often complex and require specialized sketching skills, posing challenges for rapid prototyping and generative design. We propose a framework where LLMs generate initial CAD scripts from natural language descriptions, which are then executed and refined iteratively based on error feedback. Through a series of experiments with increasing complexity, we assess the effectiveness of this approach. Our findings reveal that LLMs perform well for simple to moderately complex designs but struggle with highly constrained models, necessitating multiple refinements. The study highlights the need for improved memory retrieval, adaptive prompt engineering, and hybrid AI techniques to enhance script robustness. Future directions include integrating cloud-based execution and exploring advanced LLM capabilities to further streamline CAD automation. This work underscores the transformative potential of LLMs in design workflows while identifying critical areas for future development.
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