Design And Implementation Of Visualization System For Industrial Big Data

With the increasing competitive pressure of enterprises,the working population is slowly decreasing,the labor costs continue rising and the clients change their demand frequently.Traditional manufacturing companies are facing tremendous pressure to upgrade their industries.Only improve the efficiency and quality of products,can they gain an advantage in the competition.In order to upgrade the industry more effectively,it is necessary to import some intelligent information technologies in these enterprises,such as big data,AI and other technologies,through these technologies they can reform toward intelligent manufacturing.In the process of intelligent manufacturing,industrial big data has become an important research topic.The enterprises can be aware of bottlenecks in the production process by using industrial big data.And,through continuous optimization of these factors can optimize the efficiency and quality of products to enhance customer satisfaction.Industrial big data covers all aspects of industrial enterprises,like supply chain,logistics,warehouse,production site,and after-sales.These data will eventually become a closed loop.The product can be iteratively upgraded to optimize the quality of products by analyzing the closed loop data.This topic is mainly focus on processing of data at the production site of industrial big data.By using visualization and other analytical methods to help enterprises complete the transformation of production data visualization and accelerate the advancement to intelligent manufacturing.The paper mainly focuses on the following aspects:(1)Designed and implemented a set of TCP-based transmission protocol,which solved the problem of sticky packets problems.At the same time,it designed and implemented a set of device login authentication and dynamic encryption package to solve security issues of the device.(2)The problem of storage and push of industrial big data is solved by means of time series database and message middleware.At the same time,a set of visualization based on native application is designed and implemented to solve the performance problems of industrial big data in visualization.(3)Through RFID,data marking and data association are carried out on the key aspects of the production process.Based on this,a quality backtracking system for the manufacturing industry is realized.Through this system,data of some key stages in the production process can be obtained.(4)Through the application of the system in the cable industry,the feasibility of the system is proved.At the same time,the background management system is designed and implemented,and the materials,personnel and process parameters of the enterprise are managed uniformly,and the system is connected with the MES system for Scheduling task monitoring and other functions.