Research On Mes Data Management System Based On OPC UA

In 2013,Germany proposed the concept of "Industry 4.0",which aims to use information technology to promote the transformation of industrial production.In 2015,China formulated the "Made in China 2025" plan.In this context,providing intelligent industrial production has become one of the directions of industrial development.Since a large amount of real-time industrial data is generated during industrial production,how this data is obtained from the production line and how it is properly stored are the key issues related to the efficiency and stability of industrial systems.In this thesis,OPC UA is applied to the underlying MES as an interface for data transmission.Firstly,this thesis introduces and compares the MES data collecting methods,analyzes the data collecting needs of steel mills,and determines the data collecting objects.By analyzing and comparing the current MES-level application access to the process control devices,the OPC UA(OLE for Process Control,Unified Architecture)is applied to the underlying layer of the MES(Manufacturing Execution System)as an interface for data transmission.Then in this thesis the OPC UA client is constructed by using Node-Red visual programming,dragging and dropping related nodes.The communication between the server and client,read,write,subscription and other services are realized.Then in view of the loose structure,complex type and large amount of the industrial data,MongoDB is chosen as a database to store data.Using the sharding of MongoDB the fragmented clusters is deployed,and a data balanced distribution across the shards of the database is achieved,which increasing the horizontal scalability of the database,and by deploying replica sets,the database disaster tolerance and stability are improved.Finally,the collection and document structure are designed for the steel mill's MES.The database concurrency problems are avoided by adding optimistic locking to,and the database query is optimized by using indexes.Through the above methods,the data is transmitted from the production line to the client and then to the database,which ensures the stability and high efficiency of the system.