DocumentCode
2544307
Title
On prediction of friction coefficient using artificial neural networks
Author
Deiab, Ibrahim M. ; Al Shammari, Awadh T.
Author_Institution
Mech. Eng. Dept., American Univ. of Sharjah, Sharjah, United Arab Emirates
fYear
2009
fDate
23-26 March 2009
Firstpage
1
Lastpage
6
Abstract
Friction plays very important role in machining. It can be used to dissipate energy generated in the cutting zone and it can be used to provide extra support specially when machining flexible parts or when there is an accessibility problem. This paper investigate the application of AI schemes to predict the friction coefficient on the contact face as an alternative to running time consuming experiments, taking into accounts factors like surface roughness, material properties, etc. The results are compared with experimentally obtained data.
Keywords
cutting; friction; machining; mechanical engineering computing; neural nets; surface roughness; artificial neural networks; cutting zone; friction coefficient; machining; surface roughness; Adhesives; Artificial neural networks; Clamps; Convergence; Equations; Friction; Mechatronics; Rough surfaces; Stress; Surface roughness;
fLanguage
English
Publisher
ieee
Conference_Titel
Mechatronics and its Applications, 2009. ISMA '09. 6th International Symposium on
Conference_Location
Sharjah
Print_ISBN
978-1-4244-3480-0
Electronic_ISBN
978-1-4244-3481-7
Type
conf
DOI
10.1109/ISMA.2009.5164774
Filename
5164774
Link To Document