Surface Roughness Prediction and Cutting Parameters Optimization in High-Speed Milling AlMn1Cu Using Regression and Genetic Algorithm

摘要：

Surface roughness is an important indicator of the surface quality of machined workpieces. In this study, in order to find the functional relation between cutting parameters and surface roughness, a series of cutting experiments for AlMn1Cu are conducted to obtain surface roughness values in high-speed peripheral milling. Firstly, this paper presents the predictive mathematic model of surface roughness based on the cutting parameters. Secondly, the optimization model of cutting parameters in order to achieve the maximum material removal rate is built in this paper, and the genetic algorithm is employed to find the optimum cutting parameters leading to maximum material removal rate in the different range of surface roughnesss values.

关键词： surface roughness high-speed milling ALMn1Cu genetic algorithm

作者: Z.H. Wang J.T. Yuan X.Q. Hu W. Deng

作者单位: School of Mechanical Engineering Nanjing University of Science and Technology Nangjing, China

会议类型: 国际会议

会议名称: 2009 International Conference on Measuring Technology and Mechatronics Automation(ICMTMA 2009)(2009年检测技术与机电自动化国际会议)

会议地点: 张家界

会议语种:英文

页码: 334-337

在线出版日期: 2009-04-11（万方平台首次上网日期，不代表论文的发表时间）