Large Language Models for Manufacturing

• DOI: 10.48550/arxiv.2410.21418
• Publication Date: 2024-10-28
• Authors: Yiwei Li; Huaqin Zhao; Hanqi Jiang; Yi Pan; Zhengliang Liu; Zihao Wu; P. Shu; Jie Tian; Tangfeng Yang; Shaochen Xu; Yanjun Lyu; Parker Blenk; Jacob Pence; Jason Rupram; Eliza Banu; Ninghao Liu; L Wang; Wenli Song; Xiaoming Zhai; Ki‐Ho Song; Dajiang Zhu; B S Li; Xianqiao Wang; Tianming Liu

The rapid advances in Large Language Models (LLMs) have the potential to transform manufacturing industry, offering new opportunities optimize processes, improve efficiency, and drive innovation. This paper provides a comprehensive exploration of integration LLMs into domain, focusing on their automate enhance various aspects manufacturing, from product design development quality control, supply chain optimization, talent management. Through extensive evaluations across multiple tasks, we demonstrate remarkable capabilities state-of-the-art LLMs, such as GPT-4V, understanding executing complex instructions, extracting valuable insights vast amounts data, facilitating knowledge sharing. We also delve transformative reshaping education, automating coding enhancing robot control systems, enabling creation immersive, data-rich virtual environments through industrial metaverse. By highlighting practical applications emerging use cases this aims provide resource for professionals, researchers, decision-makers seeking harness power these technologies address real-world challenges, operational excellence, unlock sustainable growth an increasingly competitive landscape.