Prediction of MRR in Electrical Discharge Machining Process Using Artificial Neural Network Model

Shukry H. Aghdeab; Safaa kadhim Ghazi; Mostafa Adel Abdullah

Shukry H. Aghdeab Production Engineering and Metallurgy Department,University of Technology-Baghdad-Iraq
Safaa kadhim Ghazi Production Engineering and Metallurgy Department,University of Technology-Baghdad-Iraq
Mostafa Adel Abdullah Production Engineering and Metallurgy Department,University of Technology-Baghdad-Iraq

Abstract

Electrical discharge machining (EDM) is a process where the material removal of the workpiece is achieved through high frequency sparks between the electrode and the workpiece immersed into the dielectric solution. In electrical discharge machining process, the most important of cutting parameter is material removal rate (MRR). In this work, the influence of different electro discharge machining parameters (current, pulse on time and pulse off time) on the material removal rate as a result of application copper electrode to stainless steel 304, has been investigated. Artificial Neural Network Model (ANNM) of design model in MATLAB for prediction of material removal rate in electrical discharge machining. The results indicate that the Artificial Neural Network Model can be effectively used for the prediction of material removal rate with accuracy 99.69% and mean square error 0.306%."