Development and Application of Sporadic Material Inventory Optimization Management System based on Artificial Intelligence

Authors

  • Qian Li State Grid Shanxi Electric Power Company Materials Branch, Taiyuan, Shanxi, 030021 China
  • Wenjun Hou State Grid Shanxi Electric Power Company Materials Branch, Taiyuan, Shanxi, 030021 China
  • Yatong Wu State Grid Shanxi Electric Power Company Materials Branch, Taiyuan, Shanxi, 030021 China
  • Yaqi Hou State Grid Shanxi Electric Power Company Materials Branch, Taiyuan, Shanxi, 030021 China
  • Jian Zhu State Grid Shanxi Electric Power Company Materials Branch, Taiyuan, Shanxi, 030021 China

DOI:

https://doi.org/10.12694/scpe.v26i1.3536

Keywords:

Artificial intelligence; Power material optimization; Inventory optimization; Power material supply chain

Abstract

This paper introduces the overall framework of the intelligent electrical sporadic materials management system based on the ubiquitous Internet of Things. The system includes storage equipment and an intelligent management terminal. It makes optimal design for storage equipment and intelligent management terminals. The dynamic modeling of a three-layer supply chain system of power materials is constructed and composed of manufacturers, suppliers, and raw materials. The inventory control strategy of each link in the supply chain of power materials under different cooperation levels is studied by introducing the corresponding adjustment variables. Through the experiment and analysis of the system, it is proved that the system has good performance in label management, resource management, inventory management, disposal management, system management and essential management. The number of concurrent users, response speed, stability and other aspects of the system are excellent. The database is complete, independent, and secure. And the data is objectively reasonable and repairable. The system can lay a specific technical foundation for intelligent management of electrical sporadic materials.

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Published

2025-01-05

Issue

Section

Speciai Issue - Deep Learning in Healthcare