Research On Modeling And Optimization Of Milling Force In Plunge Milling Of Titanium Alloy Considering Tool Runout

With the continuous progress of society,the manufacturing industry is facing greater challenges and possibilities.The requirements for complexity,diversification,and customization require manufacturing process systems to have greater flexibility and faster reaction.Plunge milling,as a processing method that can quickly remove metal materials,has received much attention in recent years and has been widely used in aerospace and mold manufacturing industries.Milling force has a direct impact on physical quantities and phenomena such as tool wear,cutting temperature,cutting power,and machining system vibration.Correct milling force modeling and reasonable cutting parameter selection can significantly improve machining efficiency and reduce production costs.Based on this,this paper selects the difficult-to-machine titanium alloy TC4 as the test material,studies the milling force in plunge milling,and establishes two different mechanical models of the milling force considering the tool runout.With the milling force and material removal rate as the targets,a multi-objective optimization model is constructed,and a multi-objective cuckoo search algorithm is designed to obtain the Pareto optimal solution set.The main research contents of this paper include:(1)With titanium alloy TC4 as the test material,a milling force measurement system is set up,an orthogonal test is designed,and a titanium alloy plunge milling experiment is performed on a machining center to analyze the influence of cutting parameters on the maximum milling force during plunge milling.The experimental results show that the milling force becomes smaller with increase of the spindle speed,and becomes larger with increases of the cutting width,cutting step and feed per tooth.(2)The instantaneous cutting width of plunge milling based on accurate analysis of cutting geometry is calculated,and the thickness of chips is calculate considering tool runout.A milling force mechanical model with dynamic cutting force coefficients and a milling force mechanical model with cutting edge force coefficients are established respectively.The results of verification experiment show that the milling force predicted by the model have good agreement with the experiment.(3)Based on the established model,with the material removal rate and milling force as the optimization goals,a multi-objective cuckoo search algorithm is designed to optimize the Pareto optimal solution set.The optimization results are compared with the initial experimental values.The comparison results show that Algorithm-optimized models can significantly increase material removal rates and reduce milling forces.Finally,the work of this paper is summarized and prospected.