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

  • 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%."

Published
2018-01-09
How to Cite
H. Aghdeab, S., kadhim Ghazi, S., & Adel Abdullah, M. (2018). Prediction of MRR in Electrical Discharge Machining Process Using Artificial Neural Network Model. Association of Arab Universities Journal of Engineering Sciences, 25(1), 1-10. Retrieved from https://jaaru.org/index.php/auisseng/article/view/104
Section
Articles