Research on technology path and architecture of industrial large-scale model for intelligent factory in discrete industry

doi:10.12267/j.issn.2096-5931.2026.08.013

Information and Communications Technology and Policy ›› 2026, Vol. 52 ›› Issue (8): 91-96.doi: 10.12267/j.issn.2096-5931.2026.08.013

Research on technology path and architecture of industrial large-scale model for intelligent factory in discrete industry

GUO Xiaotong, XIE Runbin, WU Di, XIA Peng

Institute of Integration of Informatization and Industrialization, China Academy of Information and Communications Technology, Beijing 100191, China

Received:2026-03-23 Online:2026-08-25 Published:2026-09-02
Contact: XIA Peng

Abstract

Abstract:

Aiming at the characteristics of discrete manufacturing products, such as diverse process, frequent design changes and complex production process control, this paper defines the concept of industrial large-scale model, the core competence of industrial large-scale models for discrete industries is defined, and the mainstream technology paths of industrial large-scale models at home and abroad are reviewed. The architecture of future industrial large-scale model is proposed innovatively, which provides reference for the construction of industrial large-scale model of intelligent factory in discrete industry.

Key words: industrial large-scale model, discrete industry, smart factory, generative artificial intelligence, technology path

CLC Number:

TN929.5

GUO Xiaotong, XIE Runbin, WU Di, XIA Peng. Research on technology path and architecture of industrial large-scale model for intelligent factory in discrete industry[J]. Information and Communications Technology and Policy, 2026, 52(8): 91-96.

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http://ictp.caict.ac.cn/EN/Y2026/V52/I8/91

References 9

[1]	European Parliament and Council. Regulation (EU) 2024/1689 on laying down harmonised rules on artificial intelligence[EB/OL]. (2024-06-13)[2026-04-26]. https://eur-lex.europa.eu/eli/reg/2024/1689/oj.
[2]	Autio C, Schwarta R, Dunietz J, et al. Artificial intelligence risk management framework: generative artificial intelligence profile[EB/OL]. (2024-07-26)[2026-04-26]. https://doi.org/10.6028/NISE.AI.600-1.
[3]	Knott A, Pedreschi D, Chatila R, et al. State-of-the-art foundation AI models should be accompanied by detection mechanisms as a condition of public release[R], 2023.
[4]	杨宇田, 梁亨源, 杨宇涵, 等. 基于大模型与知识增强的工业领域智能体及其应用[C]//第36届中国过程控制会议(CPCC)会议文集. 宜宾: CPCCF, 2025.
[5]	Wen X, Zhang H, Zheng S, et al. From supervised to generative: a novel paradigm for tabular deep learning with large language models[C]//Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining(ACM SIGKDD). New York: ACM, 2024: 3323-3333.
[6]	Bjorck J, Castañeda F, Cherniadev N, et al. Gr00t n1: an open foundation model for generalist humanoid robots[PP/OL]. arXiv(2025-03-18)[2026-04-26]. https://arxiv.org.htm//2503.147341#AI.
[7]	Gemini Robotics Team, Abeyruwan S, Ainslie J, et al. Gemini robotics: bringing ai into the physical world[PP/OL]. arXiv (2025-03-25)[ 2026-04-26]. https://arxiv.org/abs/2503.20020.
[8]	Fakih M, Dharmaji R, Moghaddas Y, et al. Llm4plc:harnessing large language models for verifiable programming of plcs in industrial control systems[C]//Proceedings of the 46th International Conference on Software Engineering:Software Engineering in Practice(ICSE-SEIP). New York: ACM, 2024: 192-203.
[9]	Hui K H, Sanghi A, Rampini A, et al. Make-a-shape: a ten-million-scale 3D shape model[C]//Proceedings of the Forty-first International Conference on Machine Learning(ICML). Vienna: PMLR, 2024: 20660-20681.

Research on technology path and architecture of industrial large-scale model for intelligent factory in discrete industry

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