Supply management system based on cloud computing

Abstract

The invention discloses a supply management system based on cloud computing, and the system comprises an inventory analysis module, a processing and distribution module, and a supply evaluation module, and the processing and distribution module is used for processing and distributing a supply request initiated by a supplier for a purchase request.According to the invention, distributed processingcan be reasonably carried out on the purchasing request, slow data processing and jamming caused by huge supply management data are avoided; The supply evaluation module is used for carrying out supply evaluation on the supply request. According to the system, a purchaser can conveniently and deeply know the supplier from multiple factors, and the supplier is comprehensively and accurately judgedand evaluated; the inventory analysis module is combined with the supply allocation unit and the inventory early warning unit to analyze inventory, so that suppliers can conveniently and effectively analyze own inventory, inventory insufficiency caused by delayed replenishment and long-time warehouse-out quantity greater than warehouse-in quantity is avoided, inventory allocation is performed before inventory insufficiency, and influence on transaction due to untimely supply is avoided.

Description

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AI Technical Summary

Benefits of technology

This technology allows vendors to efficiently manage their stockpiles without overwhelming up or losing sales due to shortages during periods when they don't get enough goods needed right away. It also helps customers quickly identify which vendor best suited them based on different aspects such as how much money it holds, what kind of items there may be available more expensive compared to free space, etc., making this system useful tools against selling these products faster and easier.

Problems solved by technology

The technical problem addressed in this patented method relates to improving supply management systems for companies who use different ways to manage prices without affecting stability or reducing costs associated with maintaining accurate pricing levels. Current solutions require manual input and delayed responses during periods where there may still be enough stocked but no longer needed due to changes made overnight at peak times. This can lead to imbalances between buyings and sales requests causing delays and increased risk of financial losses. Therefore an improved solution needs to provide automated monitoring capabilities along these lines while also providing efficient asset selection strategies through Cloud Computing technology.

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