Constructing Mechanical Design Agent Based on Large Language Models

TL;DR

This paper proposes a method to build a Mechanical Design Agent using Large Language Models, aiming to enhance mechanical design processes by guiding LLM learning and reducing traditional challenges.

Contribution

It introduces a novel approach for constructing a Mechanical Design Agent based on LLMs, combining human guidance with LLM capabilities for mechanical design tasks.

Findings

Validated the method through experiments

Demonstrated improved efficiency in mechanical design tasks

Presented practical cases illustrating the approach

Abstract

Since ancient times, mechanical design aids have been developed to assist human users, aimed at improving the efficiency and effectiveness of design. However, even with the widespread use of contemporary Computer-Aided Design (CAD) systems, there are still high learning costs, repetitive work, and other challenges. In recent years, the rise of Large Language Models (LLMs) has introduced new productivity opportunities to the field of mechanical design. Yet, it remains unrealistic to rely on LLMs alone to complete mechanical design tasks directly. Through a series of explorations, we propose a method for constructing a comprehensive Mechanical Design Agent (MDA) by guiding LLM learning. To verify the validity of our proposed method, we conducted a series of experiments and presented relevant cases.