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2012 (Vol. 4, Issue: 10)
Article Information:

The Investigation of EDM Parameters on Electrode Wear Ratio

Reza Atefi, Navid Javam, Ali Razmavar and Farhad Teimoori
Corresponding Author:  Reza Atefi 

Key words:  Artificial Neural Network (ANN), Electrical Discharge Machining (EDM), electrode wear ratio, hybrid model, , ,
Vol. 4 , (10): 1295-1299
Submitted Accepted Published
December 09, 2011 January 04, 2012 May 15, 2012

Electrical Discharge Machining (EDM) is a well-established machining option for manufacturing geometrically complex or hard material parts that are extremely difficult-to-machine by conventional machining processes. The non-contact machining technique has been continuously evolving from a mere tool and die making process. In this study, the influence of different electro discharge machining parameters (current, pulse on-time, pulse off-time, arc voltage) on the electrode wear ratio as a result of application copper electrode to hot work steel DIN1.2344 has been investigated. Design of the experiment was chosen as full factorial. Artificial neural network has been used to choose proper machining parameters and to reach certain electrode wear ratio. Finally a hybrid model has been designed to reduce the artificial neural network errors. The experiment results indicated a good performance of proposed method in optimization of such a complex and non-linear problems.
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  Cite this Reference:
Reza Atefi, Navid Javam, Ali Razmavar and Farhad Teimoori, 2012. The Investigation of EDM Parameters on Electrode Wear Ratio.  Research Journal of Applied Sciences, Engineering and Technology, 4(10): 1295-1299.
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ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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