Special Issue on Generative AI for Design, Manufacturing Processes, and Materials Systems: Part II

Abstract

In this second part of the special issue, we extend the conversation beyond the foundations established in Part I, which highlighted the transformative potential of generative AI and large language models for knowledge reuse, design exploration, data fusion, and smart manufacturing operations. Articles in this second part offer insights along three complementary themes. The first theme explores how generative AI structures and manages engineering knowledge and risk. This involves leveraging large language models (LLMs), vision language models (VLMs), and knowledge graphs to turn unstructured documentation, assembly procedures, and historical recall records into actionable, validated information assets. The second theme answers how generative and deep learning models reshape design and manufacturing systems. Articles in this theme investigate new generative and deep learning approaches for geometry synthesis, control, and process monitoring that operate over high-dimensional design and signal spaces. The third theme studies how human designers collaborate with AI in creative and decision-intensive contexts. Articles in this theme examine AI in collaborative roles such as standing in for interview participants, participating in speculative design, and narrating trade-offs in multi-objective manufacturing decisions. This group of articles simultaneously introduces interesting questions regarding bias, trust, and ethics.