Inconel 718增材成形件的铣削分析及工艺参数优化

Milling analysis and optimization of process parameters for Inconel 718 additively formed parts

  • 摘要: 鉴于激光选区熔化Inconel 718成形件的表面质量和尺寸精度难以满足精密零部件的使用要求,首先,通过铣削减材后处理工艺,分析了不同铣削参数(铣削速度vc、铣削深度ap、铣削宽度ae、每齿进给量fz)组合对切削合力(F)、表面粗糙度值(Ra)的影响规律,再基于灰色关联分析方法,将多目标转化为灰色关联度(GR)单一目标优化,采用逐步回归法建立GR二阶回归预测模型,最后利用粒子群算法得到最优参数组合。结果表明,对F影响的重要性依次为fzvcapae,对Ra影响的重要性依次为fzapvcae,铣削减材后Ra最大下降97.80%,平均下降94.03%;所建立预测模型最大误差不超过5%;GR最优解为0.817 3,所对应的最优铣削工艺参数组合为vc=46.96 m/min、ap=0.25 mm、ae=2.90 mm、fz=0.025 mm/z。

     

    Abstract: In view of the fact that the surface quality and dimensional accuracy of laser selective melting Inconel 718 formed parts are difficult to meet the requirements of precision parts. Firstly, the influence of different milling parameters (milling speed vc, milling depth ap, milling width ae, feed per tooth fz) on the cutting force (F) and surface roughness (Ra) is analyzed through the milling and cutting post-processing process.Then, based on the grey relation analysismethod, the multi-objective was transformed into a single objective optimization of grey relation(GR), the second-order GR regression prediction model was established by the stepwise regression method, and finally the particle swarm optimization was used to obtain the optimal parameter combination. The results show that the importance of the influence on F is fz, vc, ap and ae, the importance of the influence on Ra is fz, ap, vc and ae respectively, and the maximum decrease of Ra is 97.80% and the average decrease is 94.03% after milling. The maximum error of the established prediction model is not more than 5%; The optimal solution of GR is 0.8173, and the corresponding optimal milling process parameter combination is vc=46.96 m/min, ap=0.25 mm, ae=2.90 mm, fz=0.025 mm/z.

     

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