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
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;
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
DOI :
10.1109/ISMA.2009.5164774
