Large Language Model-Enabled Multi-Agent Manufacturing Systems
<|reference_start|>Large Language Model-Enabled Multi-Agent Manufacturing Systems: Traditional manufacturing faces challenges adapting to dynamic environments and quickly responding to manufacturing changes. The use of multi-agent systems has improved adaptability and coordination but requires further advancements in rapid human instruction comprehension, operational adaptability, and coordination through natural language integration. Large language models like GPT-3.5 and GPT-4 enhance multi-agent manufacturing systems by enabling agents to communicate in natural language and interpret human instructions for decision-making. This research introduces a novel framework where large language models enhance the capabilities of agents in manufacturing, making them more adaptable, and capable of processing context-specific instructions. A case study demonstrates the practical application of this framework, showing how agents can effectively communicate, understand tasks, and execute manufacturing processes, including precise G-code allocation among agents. The findings highlight the importance of continuous large language model integration into multi-agent manufacturing systems and the development of sophisticated agent communication protocols for a more flexible manufacturing system.<|reference_end|>
@article{lim2024large,
    title={Large Language Model-Enabled Multi-Agent Manufacturing Systems},
    author={Jonghan Lim, Birgit Vogel-Heuser, Ilya Kovalenko},
    journal={arXiv preprint arXiv:2406.01893},
    year={2024},
    archivePrefix={arXiv},
    eprint={2406.01893},
    primaryClass={cs.MA cs.AI}
}