Knowledge sharing in manufacturing using LLM-powered tools: user study and model benchmarking

Front Artif Intell. 2024 Mar 27:7:1293084. doi: 10.3389/frai.2024.1293084. eCollection 2024.

Abstract

Recent advances in natural language processing enable more intelligent ways to support knowledge sharing in factories. In manufacturing, operating production lines has become increasingly knowledge-intensive, putting strain on a factory's capacity to train and support new operators. This paper introduces a Large Language Model (LLM)-based system designed to retrieve information from the extensive knowledge contained in factory documentation and knowledge shared by expert operators. The system aims to efficiently answer queries from operators and facilitate the sharing of new knowledge. We conducted a user study at a factory to assess its potential impact and adoption, eliciting several perceived benefits, namely, enabling quicker information retrieval and more efficient resolution of issues. However, the study also highlighted a preference for learning from a human expert when such an option is available. Furthermore, we benchmarked several commercial and open-sourced LLMs for this system. The current state-of-the-art model, GPT-4, consistently outperformed its counterparts, with open-source models trailing closely, presenting an attractive option given their data privacy and customization benefits. In summary, this work offers preliminary insights and a system design for factories considering using LLM tools for knowledge management.

Keywords: Large Language Models; benchmarking; factory; industrial settings; industry 5.0; information retrieval; knowledge sharing; natural language interface.

Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This work was supported by the European Union's Horizon 2020 research and innovation program via the project COALA “COgnitive Assisted agile manufacturing for a LAbor force supported by trustworthy Artificial Intelligence” (Grant agreement 957296).