| Issue |
MATEC Web Conf.
Volume 401, 2024
21st International Conference on Manufacturing Research (ICMR2024)
|
|
|---|---|---|
| Article Number | 10009 | |
| Number of page(s) | 8 | |
| Section | Manufacturing / Engineering Management | |
| DOI | https://doi.org/10.1051/matecconf/202440110009 | |
| Published online | 27 August 2024 | |
Industrial large model: A survey
1 Shandong University of Science and Technology, Qingdao, China
2 University of Oulu, Oulu, Finland
3 Microsoft Advanced Technology Centre, Beijing, China
4 China University of Geosciences, Beijing, China
5 Shandong Electric Power Research Institute, Jinan, China
6 Shandong University of Science and Technology, Qingdao, China
7 Xi’an University of Posts and Telecommunications, Xi’an, China
* Corresponding authors: jiehan.zhou@ieee.org; sycao5@gmail.com
Industrial large models are attracting significant attention for their roles in improving industrial production efficiency and product quality. This paper categorises and reviews current research on industrial large models in three main areas: pre-training, fine-tuning, and Retrieval-Augmented Generation (RAG). It also introduces a generic platform for industrial large models, including a model for interaction between industrial large and small models. Furthermore, it specifies the application areas of large industrial models within product lifecycle management, and discusses the challenges encountered during their development.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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