Abstract
The fast evolving Large language Models (LLMs), powered by Generative Pre-Trained Transformers (GPT), have shown revolutionary potential to transform many fields beyond natural language processing. They generate new opportunities for innovation in engineering design and manufacturing. Design and manufacturing represent critical research domains where knowledge has always been deeply embedded in engineering designers, manufacturing engineers, and technicians. LLMs can analyze, retrieve, and generate vast amount of knowledge and concepts, presenting exciting possibilities for automating tasks such as design ideation, knowledge extraction, and specification generation in design and manufacturing. However, questions emerge with regards to what types of and how much information and knowledge LLMs can extract from engineering documents and publications; how LLMs can help design concept generation and engineering problem-solving; what the best techniques and practices are to adapt LLMs in design and manufacturing. These questions require urgent attention from the research community, and their answers will provide valuable benefits to practitioners. This special issue aims to gather contributions from the computing and information engineering community to offer new insights into the application and impact of LLMs in the context of engineering design and manufacturing. The guest editor team of this special issue made a call for paper on applying LLMs in the design and manufacturing field. The diverse body of articles that comprise this special issue largely focuses on engineering design.
