Generative large language models in engineering design: opportunities and challenges

Abstract

Despite the rapid advancement of generative Large Language Models (LLMs), there is still limited understanding of their potential impacts on engineering design (ED). This study fills this gap by collecting the tasks LLMs can perform within ED, using a Natural Language Processing analysis of 15,355 ED research papers. The results lead to a framework of LLM tasks in design, classifying them for different functions of LLMs and ED phases. Our findings illuminate the opportunities and risks of using LLMs for design, offering a foundation for future research and application in this domain.