Predictive Model of Surface Roughness in High-Speed End Milling Process by Factorial Design of Experiments |
|
| Journal | Key Engineering Materials (Volume 339) |
|---|---|
| Volume | Progress of Precision Engineering and Nano Technology |
| Edited by | Shen Dong and Yingxue Yao |
| Pages | 189-194 |
| DOI | 10.4028/www.scientific.net/KEM.339.189 |
| Citation | Su Yu Wang et al., 2007, Key Engineering Materials, 339, 189 |
| Online since | May, 2007 |
| Authors | Su Yu Wang, Xing Ai, Jun Zhao |
| Keywords | High Speed End Milling, Multiple-Regression Analysis, Surface Roughness (SR) |
| Abstract | Predictive models are presented for the surface roughness in high-speed end milling of 0.45%C steel and P20 die-mould steel based on statistical test and multiple-regression analysis. The data for establishing model is derived from experiments conducted on a high-speed machining centre by factorial design of experiments. The significances of the regression equation and regression coefficients are tested in this paper. The effects of milling parameters on surface roughness are investigated by analyzing the experimental curves. |
| Full Paper | 
Get the full paper by clicking here
|
First page example
