Design And Implementation Of Tracking And Statistical Prediction System For Electronic Components Inspection Process

Informatization construction helps to improve the production efficiency and management level of enterprises and ensure the healthy development of enterprises.In some electronic components inspection enterprises,customers cannot timely grasp the progress of inspection due to the information congestion caused by network isolation.At the same time,the screening enterprises sometimes fail to complete the inspection task on time,since they cannot estimate the number of screening tasks in advance and arrange the tasks reasonably.Therefore,we can use information technology to share data safely and quickly between intranet and extranet.We also use data analysis and prediction to support task decisions in electronic component screening enterprises.This is significant to production efficiency and management level of enterprises.This thesis introduces the design and implementation of tracking and statistical prediction system for electronic components inspection process.After discussion with customers,this thesis presents the system which contains two subsystems.Considering the customer requirements of the development language,the two subsystems adopt different software system structure and technical route.The Components Inspection Process Tracking subsystem is based on C/S architecture.It designs an information transmission scheme to share information safely and quickly.It also marks and tracks the status of electronic components in the inspection process,which improves work efficiency.The modules of the subsystem mainly include Inspection Process Tracking,Certificate Management,Log Management,etc.The Inspection Process Tracking optimizes the inspection process and tracks the material status.The Certificate Management simplifies the operation steps and improves the efficiency of certificate management.Log management records user's operation information and facilitates subsequent division of accident responsibilities.The system uses QR Code,AES and Base64 to solve the problem of information sharing and low efficiency.It uses AES encryption and Base64 coding conversion to solve the share of information and the security of information.The Statistical Analysis and Prediction subsystem is based on B/S architecture.It provides support for S company's decision-making by analyzing historical data and predicting future trends.It calculates stats and plots to lighten the burden of employee.The modules of this subsystem mainly include Statistical Analysis,Cycle Calculation and Task Prediction.Statistical Analysis does the statistical calculation of historical data.Cycle calculation realizes the prediction of the electronic component detection period.Task prediction finishes the analysis of historical data and prediction of future trends.The system adopts Spring Boot,Spring MVC,My Batis and other frameworks to improve development efficiency.It uses Thymeleaf and Highcharts to realize data visualization.It also uses Nginx and Redis to improve system performance.In trend analysis and prediction,Prophet is used to analyze historical data from different components.Besides,Tensor Flow is used to train historical data and predict future trends.This system has been running for more than one year,and users' problems has been solved.It has achieved users' demand.