Milling analysis and parameter optimization for TC4 titanium alloy material
In order to investigate the influence of milling parameters on the milling force and material removal rate when machining TC4 titanium alloy material and to find the best combination of parameters,side milling experiments designed based on the orthogonal experimental method were carried out with a four-edged ball-ended milling cutter.Milling speed,feed per tooth,milling depth and milling width were chosen as variables,while milling force and material removal rate were selected as evaluation indicators.The influence laws of machining parameters on milling force and material removal rate,based on the range analysis method,were found out.The grey relational analysis(GRA)and particle swarm optimization(PSO)algorithms were adopted to optimize the milling parameters respectively,meanwhile a milling force prediction model was established based on the regression analysis method to prepare for the PSO.Finally,the two optimization methods were compared and analyzed and the prediction model was verified through the verification experiments.The results show that the prediction model established in this paper can accurately and efficiently predict the milling force,and the optimization effect of PSO is much better.
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