Surface Roughness Models and Their Experimental Validation in Micro Milling of 6061-T6 Al Alloy by Response Surface Methodology

被引:10
|
作者
Yi, Jie [1 ]
Jiao, Li [1 ]
Wang, Xibin [1 ]
Xiang, Junfeng [1 ]
Yuan, Meixia [1 ]
Gao, Shoufeng [1 ]
机构
[1] Beijing Inst Technol, Key Lab Fundamental Sci Adv Machining, Beijing 100081, Peoples R China
基金
中国国家自然科学基金;
关键词
MACHINING PARAMETERS; OPTIMIZATION;
D O I
10.1155/2015/702186
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Due to the widespread use of high-accuracy miniature and micro features or components, it is required to predict the machined surface performance of the micro milling processes. In this paper, a new predictive model of the surface roughness is established by response surface method (RSM) according to the micro milling experiment of 6061-T6 aluminum alloy which is carried out based on the central composite circumscribed (CCC) design. Then the model is used to analyze the effects of parameters on the surface roughness, and it can be concluded that the surface roughness increases with the increasing of the feed rate and the decreasing of the spindle speed. At last, based on the model the contour map of the surface roughness and material removal rate is established for optimizing the process parameters to improve the cutting efficiency with good surface roughness. The prediction results from the model have good agreement with the experimental results.
引用
收藏
页数:9
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