Latest Update (2024):

A recent update to this research is presented here: https://github.com/YuchenXia/LLM4IAS Control Industrial Automation System with Large Language Models

📄The new paper:

Y. Xia, N. Jazdi, J. Zhang, C. Shah and M. Weyrich, Control Industrial Automation System with Large Language Models, 2024, arXiv preprint. https://doi.org/10.48550/arXiv.2409.18009

GPT4IndustrialAutomation (2023/07)

This repository contains the demos of the paper "Towards an Autonomous System: A Flexible Modular Production System Enhanced with Large Language Model Agents." and "Incorporating Large Language Models into Production Systems for Enhanced Task Automation and Flexibility"

🎓📄 The peer-reviewed version of this paper has been published by IEEE after the conference IEEE-ETFA2023 (The 28th Annual Conference of the IEEE Industrial Electronics Society (IES) - The International Conference on Emerging Technologies and Factory Automation) (in Track - Artificial Intelligence for Cyber-Physical Systems in Automation), which took place on September 12th to 15th, 2023. Paper: Towards autonomous system: flexible modular production system enhanced with large language model agents

Final Published Version after Peer-Review(https://ieeexplore.ieee.org/document/10275362),

Pre-print: On Arxiv: https://arxiv.org/abs/2304.14721

🎓📄 Another paper with more design details has been presented in German VDI Automation Kongress, in Proceedings of the VDI-Berichte Nr. 2437, 2024. The conference took place on July 02nd to 03rd, 2024. Paper: Incorporating Large Language Models into Production Systems for Enhanced Task Automation and Flexibility (https://arxiv.org/abs/2407.08550).

Insight: Fine-tuned Model based on Llama-3-70B has equal performance with GPT4.

🎥 Demo Videos:

🎬 The Prompting Design:

🎬 Event-based control via function call:

More details about this event-based control mechanism can be found in Paper: Incorporating Large Language Models into Production Systems for Enhanced Task Automation and Flexibility (https://arxiv.org/abs/2407.08550).

The system overview:

The big picture:

Fine-tuned Model based on Llama-3-70B has equal performance with GPT4:

More details about the fine-tuning: Incorporating Large Language Models into Production Systems for Enhanced Task Automation and Flexibility (https://arxiv.org/abs/2407.08550)

Paper Citation

If you find the approach presented interesting and some of the ideas inspiring, please consider citing our works. We will be very glad to receive a citation, which will signal to us that there is true interest and demand.

Y. Xia, M. Shenoy, N. Jazdi and M. Weyrich, "Towards autonomous system: flexible modular production system enhanced with large language model agents," 2023 IEEE 28th International Conference on Emerging Technologies and Factory Automation (ETFA), Sinaia, Romania, 2023, pp. 1-8, doi: 10.1109/ETFA54631.2023.10275362.

@INPROCEEDINGS{10275362,
  author={Xia, Yuchen and Shenoy, Manthan and Jazdi, Nasser and Weyrich, Michael},
  booktitle={2023 IEEE 28th International Conference on Emerging Technologies and Factory Automation (ETFA)}, 
  title={Towards autonomous system: flexible modular production system enhanced with large language model agents}, 
  year={2023},
  volume={},
  number={},
  pages={1-8},
  doi={10.1109/ETFA54631.2023.10275362}}

@article{Xia2024,
   author = {Yuchen Xia and Jize Zhang and Nasser Jazdi and Michael Weyrich},
   year = {2024},
   month = {7},
   publisher = {VDI Verlag},
   title = {Incorporating Large Language Models into Production Systems for Enhanced Task Automation and Flexibility},
   url = {http://arxiv.org/abs/2407.08550},
   doi = {10.48550/arXiv.2407.08550}
}