Enterprise purchase supply chain collaborative management system

By introducing a closed-loop architecture consisting of a perception layer, a trust layer, an analysis and decision-making layer, a data security layer, and a value transformation layer into the enterprise procurement supply chain, the problems of data lag, collaboration barriers, and value disconnect are solved. This enables real-time data collection, dynamic credit management, and instant value transformation, thereby improving the transparency, security, and efficiency of the supply chain.

CN122088931APending Publication Date: 2026-05-26四川工业科技学院
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Patent Information

Application Number
CN202610146740.9
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-02-02
Publication Date
2026-05-26

AI Technical Summary

Technical Problem

Existing technologies in enterprise procurement supply chain management suffer from problems such as data lag, collaboration barriers, and value disconnect. This results in data collection that is not real-time, prone to errors, and difficult to trace. Identity verification is at risk of being impersonated, access control is rigid, and predictive early warning of equipment status and global simulation optimization of operational strategies cannot be achieved. Environmental performance and economic benefits are seriously disconnected.

Method used

It adopts a closed-loop architecture consisting of a perception layer, a trust layer, an analysis and decision-making layer, a data security layer, and a value transformation layer. Through passive RFID tags, self-organizing networks, edge computing, federated learning, and biometric identification technologies, it realizes automatic data collection, real-time analysis, dynamic access control, cross-enterprise credit assessment, and instant value transformation.

Benefits of technology

It enables real-time, reliable data collection and synchronization across the entire process, dynamic credit rating and access control, rapid identification of equipment anomalies, secure cross-enterprise data collaboration, and immediate conversion of green practices into economic benefits, thereby improving the transparency, efficiency and sustainability of the supply chain.

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Abstract

The invention discloses an enterprise purchase supply chain collaborative management system, and the system comprises a sensing layer which is disposed at each node of a purchase supply chain, and is used for collecting the circulation and processing data of renewable resource materials through a built-in passive RFID tag of heterogeneous equipment, and carrying out the data verification and synchronization through an ad hoc network between the equipment; the credible layer is used for binding the biological characteristic information of the operator with the identity, the operation authority and the initial credit rating, and dynamically managing credit and cross-enterprise authority based on the operation behavior and equipment feedback; the analysis decision-making layer is used for carrying out analysis and early warning on the sensing data through an edge calculation module and simulating value conversion paths under different working conditions through a virtual mapping model, the calculation module is deployed at the edge of the network, data can be processed nearby, equipment faults, quality deviation and other abnormalities can be independently and rapidly recognized, early warning is carried out, and the method is suitable for large-scale popularization and application. And the crossing from post-event response to pre-event prediction and in-event intervention is realized.
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