Research On Data Modeling,integration And Storage Technology For Production Process Management And Control

The discrete workshop production process management and control system monitors and analyzes key production resource in real time from multiple dimensions such as equipment execution,production-line scheduling,and workshop planning,and visualizes the analysis results to assist production managers in decision-making.Production process data is the core object of the system.Therefore,ensuring technical implementation of data modeling,data collection,and data storage is the key to achieve intelligent management and control of the production process.However,non-universal data description model,high interfaces maintenance cost and inefficient storage architecture obstacles the smooth implementation of the system.This paper introduces data modeling technology,data communication technology and big data technology into the research for the above problems,and develops a production process management and control system.The deployment and operation of the system improves the transparency of the production process and provides new ideas for the digital construction of discrete workshops.The research content and contributions of this article are as follows:(1)Based on the analysis of the discrete workshop production process business flow,discrete workshop production process data hierarchy is built to clarify the business objects for the production process management and control system.Then,the production process data model is constructed using UML to achieve a unified expression for the attribute,layer,association of production process data.Then,the data model is instantiated through XML to provide a standard data structure for data integration and storage in the production process.(2)Incremental data integration technology for heterogeneous workshop systems is proposed.For real-time data,streaming data collection based on the communication adaptation layer is adopted.On the basis of research on data interface adaptation,communication parameter configuration,and communication interface call,the interface adaptation and real-time data collection is realized;for non-real-time data/static data,offline Data batch integration based on Data X is adopted.The batch migration of offline production data is realized with the design of ETL architecture and the construction of ETL parameter configuration model.(3)A data storage architecture based on HDFS-HBase-MySQL is proposed,and the physical storage structure of production process data is designed to achieve homogeneous storage of production process data.Then,a data analysis architecture based on Hive-Spark is proposed to support analysis and application of mass storage data.(4)Taking a discrete workshop as an example,a Hadoop cluster for the workshop is built,and a production process management and control system is designed and developed.The system is deployed and tested on the workshop,and the test results verify the feasibility and effectiveness of the method proposed in this paper,which can provide technical support for the smooth implementation of the production process control system.