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2013 (Vol. 6, Issue: 11)
Article Information:

Artificial Neural Network Modeling of Surface Roughness in Magnetic Abrasive Finishing Process

F. Djavanroodi
Corresponding Author:  F. Djavanroodi 

Key words:  Artificial neural network, brass finishing, magnetic abrasive, surface roughness, , ,
Vol. 6 , (11): 1976-1983
Submitted Accepted Published
November 24, 2012 January 01, 2013 July 25, 2013
Abstract:

Magnetic Abrasive Finishing (MAF) is an advanced finishing process in which the cutting force is controlled by magnetic field and it provides a high level of surface finish and close tolerances for wide range of industrial application. In this study the parameter that affects surface roughness in MAF process on a brass shaft of CuZn37 have been examined experimentally. These parameters are: intensity of the magnetic field, work-piece velocity and finishing time. It has been shown that the intensity of magnetic field has the most effect on finishing process, a higher intensity in magnetic field, results in a higher change in surface roughness, increasing finishing time results in decreased surface roughness and a lower work-piece velocity leads to a lower surface roughness. Finally Artificial Neural Network (ANN) prediction of surface roughness are carried out and compared with experiment. It was found that the coefficient of multiple determinations (R2-value) between the experimental and ANN predicted data is equal to about 0.999, therefore, indicating the possibility of ANN as a strong tool in simulating and prediction of surface roughness in MAF process.
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  Cite this Reference:
F. Djavanroodi, 2013. Artificial Neural Network Modeling of Surface Roughness in Magnetic Abrasive Finishing Process.  Research Journal of Applied Sciences, Engineering and Technology, 6(11): 1976-1983.
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ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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