Design And Research Of Intelligent Production Line Of Press Pump Based On MES

At present,China’s manufacturing industry is facing a series of problems such as backward production equipment,high manufacturing costs,low quality,rough production processes,and insufficient independent innovation capabilities of enterprises.Manufacturing execution system(MES),as a product of enterprise informationization and industrialization,is a feasible solution to realize factory intelligence,and has been rapidly development by some policies such as "Made in China 2025" and German "Industry 4.0".This paper takes the main functions in the discrete manufacturing Industry in MES as the research object,To analyzes and studies related technologies and theories.Realizing the interconnection of all equipment in the workshop is the first step for enterprises to become intelligent in the factory.Analyzing this problems that often occur during the wiring of discrete manufacturing workshops,based on OPC,Socket,Arduino and other technologies and using WIFI serial server The wireless connection between the equipment and the MES is realized,and the problem of wiring difficulties in the discrete workshop is reasonably solved,and laid the foundation for enterprises to realize intelligent production.Product quality prediction has long been one of the most concerned topics for enterprises.Therefore,in the design process of MES,the product quality prediction module is used as one of the core modules of MES for research and development.BP neural network is relatively mature in the field of prediction,but it also has the disadvantages of slow learning convergence and inability to guarantee that the convergence reaches the global minimum.In this paper,the BP neural network is the core algorithm of the compression pump quality prediction module.The weights and thresholds of the BP neural network algorithm are optimized by genetic algorithms.Finally,the product quality prediction is made based on the actual data of the compression pump production workshop.Feasibility of production workshop.The current scheduling method of the press pump production workshop is traditional manual scheduling.This method cannot always complete the task efficiently when the order demand is large or other unexpected conditions occur.In this paper,the genetic algorithm is used as the core algorithm of the scheduling module of the press pump production workshop.Based on the shortcomings of the algorithm,such as premature maturity and slow local convergence,the algorithm is optimized using fitness value calibration,adaptive crossover,and mutation design.The actual data of the workshop was used to conduct scheduling experiments,which proved the feasibility of the MES module in the press pump production workshop.Based on the above theoretical scheme,this paper uses Visual Studio 2017 as the core development software of the MES,Sql Server 2017 is the database of MES,and Matlab 2017 is the calculation tool.Designed and developed a structure of C/S MES.Through actual tests,it is verified that the MES system can meet the needs of the enterprise,effectively improving the management level of the production workshop and the production efficiency of the pressing pump.