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Article type: Research Article
Authors: Li, Ruia | Zhao, Fenga | Zhao, Boyub; c; *
Affiliations: [a] School of Digital Commerce, Zhejiang Yuexiu University, Shaoxing, China | [b] Lishui University Business School, Lishui, China | [c] School of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing, China
Correspondence: [*] Corresponding author: Boyu Zhao, School of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 212000, China. E-mail: [email protected].
Abstract: In the context of global economic integration and Industry 4.0, digital manufacturing has become crucial. As one of the economic cores of China, the digitization process of the manufacturing industry in the Yangtze River Delta is particularly critical to the overall economic growth. Based on the theory of Industry 4.0 and digital manufacturing, this study deeply analyzes the current digital development of the manufacturing industry in the Yangtze River Delta. More importantly, this paper successfully constructs a fuzzy control model to quantitatively evaluate and guide the process of digital transformation of manufacturing industry in this region. The empirical results of the model reveal how key factors such as capital, talent, technology and data security affect the digitization process, and provide concrete and operational transformation strategies for the Yangtze River Delta region. In addition, combined with industrial advantages, policy support, technological progress and market demand, this paper predicts the digital development prospects of the manufacturing industry in the Yangtze River Delta. Overall, the study not only provides in-depth insights on the digitization of manufacturing in the Yangtze River Delta, but also provides practical guidance for actual operation, which has high theoretical and practical value.
Keywords: Digital manufacturing, the yangtze river delta, development of manufacturing industry, challenge and possibility
DOI: 10.3233/JCM-247495
Journal: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 4-5, pp. 2657-2671, 2024
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