Metallurgical industry data management system and method

Abstract

The invention provides a metallurgical industry data management system and method, and the system comprises a data definition module which defines static data and dynamic data, and carries out the classification of the data at the same time, and the classification comprises the steps: carrying out the preliminary classification of the data according to the flow of a production line, and carrying out the secondary classification of a preliminary classification result according to the flow and the equipment type; a data acquisition module which is used for acquiring the dynamic data; a data distribution module which is used for caching the acquired data and pushing the data; a data processing module which comprises an event triggering unit, a data statistics unit and a data filtering unit used for filtering data. According to the invention, data standardization is taken as a core, and functions of data acquisition, storage and the like are performed on the basis of specification definition according to data characteristics of the iron and steel industry, so that data aggregation and sharing are realized, an island phenomenon of data dispersion is avoided, and data capitalization becomes simple.

Description

technical field [0001] The invention relates to the field of metallurgy and the field of computer application, in particular to a metallurgical industry data management system and method. Background technique [0002] The automation and informatization level of process units in the iron and steel industry is relatively high, and the system structure is complex. Its production process is a typical big data production process, and the iron and steel industry data contains huge hidden values ​​such as technology, control, experience, supply and demand, etc. Design and construction of unified data The management platform gathers, manages, and uses the data of various systems in the production line in a standardized manner, which is the basic requirement of intelligent manufacturing. Based on this, production operations can be optimized, production abnormality analysis and resolution capabilities can be strengthened, and production efficiency and quality can be improved. [0003]...

AI Technical Summary

Problems solved by technology

[0005] Because the traditional method mainly uses a single computer and server hard disk media for data storage, on the one hand, the capacity is limited, and on the other hand, in order to ensure the access efficiency of online data, the data is usually backed up and transferred regularly, resulting in the phenomenon of being discarded or discarded. serious

[0006] 2) Data is scattered, and the phenomenon of isolated islands is serious

At the same time, different service providers usually provide different data storage methods, and are unwilling to provide interfaces to third parties.

[0008] 3) Lack of data specification, high cost of understanding and reuse

[0009] The design and construction of iron and steel production lines are complex, with many participating units, and the definitions of data in each system are self-contained. It is extremely difficult to integrate new applications and utilize existing data. The cost of finding and understanding data and secondary applications is high, resulting in Appears to exist but is not very usable

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