Real-time Data Processing Applications In Steel Production Quality Control

As the advance of information technology on industrial information system, thescale of data acquisition is being extended, the accuracy and speed of data acquisitionare improved. Real-time data stream has become increasingly widespread in industrialproduction. However, most of the current data analysis methods of industrial real-timedatabase are offline and static, and the data analysis of these data is limited in extractingpreliminary information. The traditional analysis and processing based on static data isunable to meet the needs of enterprise applications in real-time data processing. In theiron and steel enterprises, product online quality analysis combined with the productionplanning data and production real-time data stream is an urgent problem.This thesis proposed a complete plant-level real-time data acquisition, storage, andtreatment solutions to solve the problems steel producers currently have that cannotcombine massive real-time data processing effectively with real-time monitoring of thewhole plant and product online quality management. In addition, this thesisimplemented enterprise data integration platform to achieve real-time integration,sharing and correlation calculating between real-time data, enterprise product data andother subsystems’ data. Based on the platform, this thesis implemented product onlinereal-time monitoring and product quality online analysis system. The system is mainlyto solve problems that production real-time monitoring, over limit alarm, real-time dataprocessing and product online quality judgment etc. Furthermore, according to theenterprise application circumstances, this thesis proposed a series of systemoptimization solutions and it ensures the efficiency of the system. Application resultsshow that the solution effectively solved problems of real-time data processing andensured the efficiency of production monitoring and quality control, thus bring hugeeconomic benefits to enterprise.