Construction of a surface roughness prediction model for high speed machining |
| |
Authors: | S Y Lin S H Cheng C K Chang |
| |
Affiliation: | (1) Mechanical Engineering Department, Indian Institute of Technology, Delhi, New Delhi, -110016, India; |
| |
Abstract: | In manufacturing environment prediction of surface roughness is very important for product quality and production time. For
this purpose, the finite element method and neural network is coupled to construct a surface roughness prediction model for
high-speed machining. A finite element method based code is utilized to simulate the high-speed machining in which the cutting
tool is incrementally advanced forward step by step during the cutting processes under various conditions of tool geometries
(rake angle, edge radius) and cutting parameters (yielding strength, cutting speed, feed rate). The influences of the above
cutting conditions on surface roughness variations are thus investigated. Moreover, the abductive neural networks are applied
to synthesize the data sets obtained from the numerical calculations. Consequently, a quantitative prediction model is established
for the relationship between the cutting variables and surface roughness in the process of high-speed machining. The surface
roughness obtained from the calculations is compared with the experimental results conducted in the laboratory and with other
research studies. Their agreements are quite well and the accuracy of the developed methodology may be verified accordingly.
The simulation results also show that feed rate is the most important cutting variable dominating the surface roughness state. |
| |
Keywords: | |
本文献已被 SpringerLink 等数据库收录! |
|