Manufacturing enterprise demand management and data processing system and method based on cloud server

Abstract

The invention discloses a manufacturing enterprise demand management and data processing system and method based on a cloud server. The system comprises a factory layer and a platform layer. The factory layer is used for enhancing data relevance, security and coordination of enterprises. The factory layer comprises a factory server, a switch, a workshop data workstation and a production unit. Theplatform layer is used for coordinating internal / external resources of enterprises to provide services for the enterprises. The platform layer comprises a cloud server, a mobile terminal layer, a resource allocation platform layer and a resource service layer. The resource allocation platform layer is used for providing a data interface for the connection of the mobile terminal layer, the resourceservice layer and the cloud server. According to the invention, the safe and efficient transmission of data is realized through the factory layer and the data relevance, coordination and safety of each production unit are improved and the operation pressure of the server is reduced. The resource allocation efficiency is improved, the efficiency of enterprise production is improved, and the cost is reduced.

Description

technical field [0001] The present invention relates to the technical field of enterprise management and enterprise data processing, in particular to a cloud server-based manufacturing enterprise demand management and data processing system and method. Background technique [0002] With the improvement of the numerical control level of production equipment, testing equipment and other equipment of manufacturing enterprises, the level of informatization of production lines has also improved. There are more and more auxiliary equipment around the main production equipment. In order to obtain the data of the main production equipment and auxiliary equipment, the wiring of the production workshop is more and more. In particular, the data format and data transmission protocol of various devices are not unified, resulting in all devices sending data to the server through the switch for processing. This method of directly collecting data through the switch, and collecting many devi...

AI Technical Summary

Problems solved by technology

In this way, data such as the production operation and process parameters of the enterprise are also sent to the external network, which poses a security risk to the core data such as the production operation and process parameters of the enterprise.

In addition, the utilization rate of enterprise resources is low. For production enterprises, resources include human resources (equipment experts, process experts, management experts, technical experts, etc.), supplier resources (tool / measurement / fixture / auxiliary suppliers, raw material suppliers) , spare parts suppliers, etc.), core component remanufacturing base resources, etc. Too many of these resources make it difficult for enterprises to optimize management, and the deployment efficiency of various resources is poor, which cannot improve production efficiency and reduce costs for enterprises; for example, human resources Experts in various fields cannot provide better services for enterprises through efficient collocation. The traditional talent collocation service method is usually that experts in various fields provide services for enterprises through high-frequency meetings, discussions and exchanges. However, this method is not only inefficient, but also time-consuming.

Images