Research On Digital Twin Model For NC Milling And Optimization Of Machining Parameters For Energy Efficiency

Digital twin is one of the hot technologies driving intelligent manufacturing.It can establish the connection between physical space and virtual space,so that they can feed back data and information to each other.It is the best way to realize the interaction and integration between physical factory and virtual factory.Comprehensive implementation of green manufacturing is also one of the future trends of the manufacturing industry.At present,China has become the world’s largest country that produces and consumes machine tools.Therefore,to improve the energy efficiency of machine tool machining is a urgent problem facing China’s manufacturing industry,which is great significance to save energy.In this paper,the hardware device data-driven digital twin virtual model and the energy-oriented NC milling parameters optimization are studied,and the client is developed.It provides a certain support for exploring the new intelligent manufacturing mode and improving the energy efficiency of NC machine tools.Firstly,the digital twin model of NC milling is studied.Data transmission is realized through communication protocols such as S7 communication,Socket communication and Web service,and data access to industrial robots,AGV vehicles and CNC machining centers is realized through scripts.The virtual model is driven by real-time data from hardware devices.Complete the mapping of virtual space to physical space.Secondly,the optimization of processing parameters for energy efficiency is studied.The energy consumption characteristics of NC machining system are analyzed,the models of no-load energy consumption,auxiliary energy consumption and cutting energy consumption of machining center are established,and the energy efficiency function of NC milling is established.In order to reveal the influence of machining parameters on the energy efficiency of machining center,the milling experiment is carried out in XKN713 vertical machining center,and the prediction model of energy efficiency is established and the accuracy of the prediction model is verified by experiments.On this basis,a NC milling parameter optimization model is established,which takes spindle speed,feed speed,cutting depth and cutting width as optimization variables and energy efficiency as optimization objective.The genetic algorithm written in python language is used to solve the above model,and the optimized machining parameters are obtained,which improves the energy efficiency of the machining center.Finally,a simulation analysis model is called in the Unity 3D platform to develop the user interaction interface.By acquiring real-time processing parameters and optimizing them,optimization suggestions are given.Through the actual operation,two functions of real-time data-driven virtual model and numerical control milling parameters optimization can be realized.