| With the high strength, heat resistance, corrosion resistance and other advantages, Austenitic stainless steel are widely used in various industries such as aviation industry, chemical industry, petroleum industry, construction industry and food industry. However, when machining this kind of material, severe work hardening and serious tool wear and damage are generally occurred. According to the hard machinability of austenitic stainless steels, aiming to improve machining quality and efficiency, and in order to reduce production costs, the cutting parameters of finish face milling304austenitic stainless steel were optimized through experimental methods, detailed study about surface roughness, cutting force, spindle acceleration tool life and tool failure mechanism were carried out in this thesis. On this basis, in order to further optimize the cutting process and parameters, face milling dynamics model was build according to experimental data, and milling stability region was calculated. Cutting temperature was analyzed with simulation by establishing effective AdvantEdge three-dimensional finite element simulation model.In this thesis, surface roughness, cutting force and spindle acceleration were selected as optimization index for researching machinability of face milling austenitic stainless steel. The optimized range of cutting parameters obtained by orthogonal experimental results were as follows:cutting speed(v):120-160m/min, feed per tooth(fz):0.08-0.12mm/z, axial depth of cut(ap):0.6-1mm, radial depth of cut (ae):32-40mm, optimum extended length was50mm. It was noticed that various cutting parameters had different influence on surface roughness, cutting force and spindle acceleration. By comprehensive analysis of experimental results, it was concluded that cutting speed had the greatest influence of all, which should not be too high, feed per tooth and axial depth of cut followed by, and the radial depth of cut had the least influence.In the experiments, cutting tool life was measured and tool wear mechanisms were analyzed under different cutting parameters, and different tool wear curves were obtained in different cutting speeds. At lower speed, the process of tool wear included three stages:initial wear, normal stabilized wear and rapid wear. At higher speed, the tool wear curves seemed like linear law. The tool life was the longest when cutting parameters were v:80m/min, fz:0.08mm/z, ap:0.6mm, and the material removal volume was largest when cutting parameters were v:200m/min, fz:0.08mm/z, ap:1mm. At different cutting parameters, tool rake face wear was slight, while tool flank wear was serious, and tool failure mode was boundary wear, the mechanisms of flank wear contained abrasive wear, adhesive wear, oxidation wear and diffusion wear.In order to further optimize the cutting process, dynamics model of face milling austenitic stainless steel was established, and Matlab/Simulink tool was used to predict the cutting force and vibration signals. Dynamics model was proved effective after comparing cutting force experimental results with predicted results. In order to improve the stability of the milling process, stability region were calculated, the results showed that the proper parameters were as follows:feed per tooth was0.08-0.12mm/z, radial depth of cut was35-45mm, tool extended length was50mm, cutting speed was80-240m/min, and axial depth of cut should be less than1.2mm.AdvantEdge FEM software was used to establish a three-dimensional finite element simulation model of face milling austenitic stainless steel. Cutting force and chip simulation results were in agreement with the experimental results, which proved the effectiveness of the model. Cutting temperatures under different parameters were analyzed by this simulation model. Simulation results showed that the highest temperature region in the cutting zone was near the cutting tool nose; temperature distribution on the tool rake face, flank face and interior temperature showed in an obvious gradient manner; two peaks of cutting temperature were distributed along the cutting edge of tool, and the area where temperature peaks occurred was just the position where the serious tool wear happened during the experiment. Cutting temperature changed greatly during the process of tool’s cutting in and cutting out, showing the periodical thermal shock; temperature was increased with the increase of cutting speed and feed per tooth as well as axial depth of cut. It was concluded by the simulation results that the highest cutting temperature first increased and then decreased with the increase of axial rake angle and radial rake angle, the final optimized axial rake angle was20°,and the optimum radial rake angle was0°. |
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