Smart Audit System Empowered by LLM
<|reference_start|>Smart Audit System Empowered by LLM: Manufacturing quality audits are pivotal for ensuring high product standards in mass production environments. Traditional auditing processes, however, are labor-intensive and reliant on human expertise, posing challenges in maintaining transparency, accountability, and continuous improvement across complex global supply chains. To address these challenges, we propose a smart audit system empowered by large language models (LLMs). Our approach introduces three innovations: a dynamic risk assessment model that streamlines audit procedures and optimizes resource allocation; a manufacturing compliance copilot that enhances data processing, retrieval, and evaluation for a self-evolving manufacturing knowledge base; and a Re-act framework commonality analysis agent that provides real-time, customized analysis to empower engineers with insights for supplier improvement. These enhancements elevate audit efficiency and effectiveness, with testing scenarios demonstrating an improvement of over 24%.<|reference_end|>
@article{yao2024smart,
    title={Smart Audit System Empowered by LLM},
    author={Xu Yao, Xiaoxu Wu, Xi Li, Huan Xu, Chenlei Li, Ping Huang, Si Li,
  Xiaoning Ma, Jiulong Shan},
    journal={arXiv preprint arXiv:2410.07677},
    year={2024},
    archivePrefix={arXiv},
    eprint={2410.07677},
    primaryClass={cs.CL}
}