M. Chandrasekaran and D. Devarasiddappa
Development of Predictive Model for Surface Roughness in End Milling of AlSiCp Metal Matrix Composites using Fuzzy Logic
1292 - 1297
2012
6
7
International Journal of Mechanical and Mechatronics Engineering
https://publications.waset.org/pdf/12908
https://publications.waset.org/vol/67
World Academy of Science, Engineering and Technology
Metal matrix composites have been increasingly used
as materials for components in automotive and aerospace industries
because of their improved properties compared with nonreinforced
alloys. During machining the selection of appropriate machining
parameters to produce job for desired surface roughness is of great
concern considering the economy of manufacturing process. In this
study, a surface roughness prediction model using fuzzy logic is
developed for end milling of AlSiCp metal matrix composite
component using carbide end mill cutter. The surface roughness is
modeled as a function of spindle speed (N), feed rate (f), depth of cut
(d) and the SiCp percentage (S). The predicted values surface
roughness is compared with experimental result. The model predicts
average percentage error as 4.56 and mean square error as 0.0729.
It is observed that surface roughness is most influenced by feed rate,
spindle speed and SiC percentage. Depth of cut has least influence.
Open Science Index 67, 2012