Surface texture features such as surface morphology and surface roughness control the corrosion resistance and fatigue resistance of parts. Due to the complex structure of tool and workpiece in milling process, the tr...
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Surface texture features such as surface morphology and surface roughness control the corrosion resistance and fatigue resistance of parts. Due to the complex structure of tool and workpiece in milling process, the traditional experimental method is not suitable. Based on the cutting edge line model, the tool trajectory model and the point cloud model of the convex surface workpiece, the simulation model of the surface topography and surface roughness of the convex surface hardened steel mold milling process was established, and the simulation of the surface topography and roughness was realized by combining with the z-map simulation algorithm. The correctness of the model is proved by the confirmatory experiment. Based on Taguchi method and gray relation analysis method, the sensitivity of surface roughness to machining inclination and cutting parameters is analyzed. It is concluded that the spindle speed has the greatest influence on the roughness and the roll angle has the least influence. The research results provide a theoretical basis for the optimization of cutting parameters in the machining process.
With the aim of improving the machined surface quality of die steel, this paper takes Cr12MoV quenched die steel as the research object and proposes a ball head milling surface morphology prediction model that compreh...
详细信息
With the aim of improving the machined surface quality of die steel, this paper takes Cr12MoV quenched die steel as the research object and proposes a ball head milling surface morphology prediction model that comprehensively considers influencing factors, including tool vibration, eccentricity, as well as deformation. By setting key parameters, such as line spacing, feed per tooth, cutting depth, and phase difference, the system analyzed the influence of each parameter on the residual height and surface roughness of the machined surface. High-speed milling experiments were conducted, and the surface morphology of the samples was observed and measured under a microscope. The simulation results show good agreement with the experimental data, with errors within 7%~15%, proving the accuracy of the model. This study can provide theoretical support and methodological guidance for surface quality control and processing parameter optimization in complex mold surface machining.
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