现代制造工程 ›› 2018, Vol. 457 ›› Issue (10): 51-56.doi: 10.16731/j.cnki.1671-3133.2018.10.008

• 增材制造 • 上一篇    下一篇

激光选区熔化成型件铣削表面粗糙度预测模型及参数优化研究

陈曦1,2, 蒋国璋1,2, 段现银1,2   

  1. 1 武汉科技大学冶金装备及其控制教育部重点实验室,武汉 430081;
    2 武汉科技大学机械传动与制造工程湖北省重点实验室,武汉 430081
  • 收稿日期:2017-06-30 出版日期:2018-10-20 发布日期:2019-01-07
  • 作者简介:陈曦,硕士研究生,研究方向为现代加工工艺。段现银,通信作者,讲师,研究方向为智能制造。E-mail:857796441@qq.com
  • 基金资助:
    国家自然科学基金资助项目(51605346)

The milling surface roughness prediction model and parameter optimization research of selective laser melting components

Chen Xi1,2, Jiang Guozhang1,2, Duan Xianyin1,2   

  1. 1 Key Laboratory of Metallurgical Equipment and Control Technology,Ministry of Education, Wuhan University of Science and Technology,Wuhan 430081,China;
    2 Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering, Wuhan University of Science and Technology,Wuhan 430081,China
  • Received:2017-06-30 Online:2018-10-20 Published:2019-01-07

摘要: 针对激光选区熔化(SLM)316L不锈钢成型件表面质量无法满足装配精度,仍需进行铣削加工的要求,设计正交试验方案,并将铣削路径与激光扫描路径的夹角作为表面粗糙度影响因素之一,利用多元回归分析法,建立铣削参数预测模型,并对该模型进行回归方程和回归系数显著性检验,结果表明,夹角、每齿进给量、铣削速度和铣削深度对表面粗糙度的影响均显著,但夹角的显著性F检验结果仅约为每齿进给量检验结果的1/8。模型的预测结果可为SLM复杂结构件在加工中提供铣削参数选择依据,并为增减材制造提供理论基础。最后使用粒子群算法,找到最佳的铣削参数,从而提高加工的表面质量。

关键词: 激光选区熔化, 316L不锈钢, 铣削参数, 表面粗糙度

Abstract: To meet the requirement that selective laser melting 316L stainless steel components needs milling process to improve its surface quality,a mathematical model of surface roughness is founded based on orthogonal experiment to optimize the milling parameters,which gives a basis to choose appropriate milling parameters of selective laser melting 316L stainless steel components,and the angle between the milling path and laser scanning path,as one of the surface roughness influencing factors,has been taken into account.Based on multiple linear regression analysis,milling parameter model was established.The significant tests of regression equation and regression coefficient are conducted and it is proved that the influence of the angle,the feed per tooth,milling speed and milling depth were significant,but in the significant F-measure,the angle is only about 1/8 times the feed per tooth.The prediction results of the model can provide the basis for the selection of milling parameters of the SLM complex structure in the actual production,and provide the theoretical basis for the hybrid manufacturing.Finally,the particle swarm optimization algorithm is used to find the optimal milling parameters to improve the surface quality.

Key words: selective laser melting, 316L stainless steel, milling parameters, surface roughness

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