Intelligent Investigation of Manufacturing Supply Chain Management System Based on Industrial Big Data

Authors

  • He Yu Changchun College of Electronic Technology, Changchun 130000, Jilin, China

Abstract

In today’s society, supply chain management systems are becoming more widely used, and their complexity is increasing. Suppliers and customers are distributed all over the world, leading to the traditional manufacturing supply chain management system being unable to operate optimally in the global context. Therefore, this current study uses industrial big data technology to examine the intellectualization of the manufacturing supply chain management system. Taking the supply chain management system of B manufacturing enterprise as an example, the study first determined the procurement process of the supply chain. Based on the comparison between common procurement quantities and actual demand results, it showed that the intelligent model of the system had stronger capture ability than traditional supply chain management systems, could timely understand market changes, and reduced procurement losses. The procurement volume was close to the actual demand. Secondly, the production process of the supply chain was examined. Based on the comparison of the total production quantity and qualified quantity results of the workshop within the specified time, it was found that the intelligent model of the system had higher production efficiency and quality every time compared to traditional supply chain management systems, especially with a production qualification rate exceeding 0.95 every time. Next, the warehousing process of the supply chain was examined. Based on the comparison of each count duration and the number of invalid counts, it was found that the total count duration
of the system’s intelligent model ranged from 30 minutes to 34 minutes, and the number of invalid counts for each experiment ranged from 1 to 5. The efficiency of each inventory was higher than that of traditional supply chain management systems. Finally, the logistics link of the supply chain was determined. Based on the comparison of logistics accuracy and logistics cost results, it was found that the logistics accuracy of traditional supply chain management systems was lower than 80%, while the logistics accuracy of intelligent system models was higher than 80%. The logistics costs generated by the intelligent system model were less than those generated by traditional supply chain management systems.

Keywords: supply chain management system; industrial big data; system intelligence; data acquisition and pre-processing; modeling analysis; decision support

Cite As

H. Yu, "Intelligent Investigation of Manufacturing Supply Chain Management System Based on Industrial Big Data",
Engineering Intelligent Systems, vol. 34 no. 4, pp. 511-521, 2026.


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Published

2026-07-01

Issue

Vol. 34 No. 4 (2026): International Journal of Engineering Intelligent Systems

Section

Article

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