Study On Parameter Optimization Of Milling Zirconia Ceramics With PCD Cutting Tools

In order to solve the problems of poor surface quality,low efficiency and high cost,the influence of the machining parameters on cutting force,tool wear and material removal rate in the process of milling zirconia ceramics by polycrystalline diamond(PCD)tools was studied with finite element simulation software.A set of optimal parameter combinations of cutting force,tool wear and material removal rate were obtained.First,a processing model of PCD tool milling zirconia ceramics was built with ABAQUS finite element software.The spindle speed,feed rate,radial depth of cut and axial depth of cut were determined as influencing factors,and the simulation scheme was designed by using the central compound design method.The simulation data of the response performance index based on cutting force,tool wear and material removal rate was obtained.And it was analyzed by variance analysis and reliability test.The results showed that the confidence level of the second-order response surface model for cutting force,tool wear and material removal rate was higher than 0.92.The response surface plot and contour plot of the interaction of four factors on cutting force,tool wear and material removal rate were plotted.The influence law of spindle speed,feed rate,radial depth of cut and axial depth of cut and their interaction on cutting force,tool wear and material removal rate were obtained,which were consistent with the results of variance analysis.A multi-objective optimization model was built,and a set of optimal machining parameter combinations which minimized cutting force and tool wear and maximized material removal rate were obtained.The spindle speed was 8000r/min;the feed speed was 90.65mm/min;the radial depth of cut was 0.10mm;and the axial depth of cut was1.37mm.Under this condition,when the milling length was 60mm,the cutting force was234.81N;the tool wear was 35.48μm;and the material removal rate was 12.67mm~3/min.Finally,the reliability of the optimization model was verified through comparative experiments and verification experiments.Figure 29;Table 17;Reference 78...