AI based Modeling of Quality Parameter in EDM using Advanced Material for Energy Optimization

Abstract

Titanium superalloy is most widely used in aircraft, spacecraft, naval ships, missiles and many other important industries due to its superior mechanical properties. The unconventional machining processes (UMPs) are the best manufacturing methods to shape these types of materials. Electrical discharge machining (EDM) is one of such thermal energy based UMP which has been widely accepted for machining of Titanium alloy. In the present research the EDM has been carried out in Ti-6Al-4V alloy by varying peak current, pulse-on time and pulse-off time to evaluate material removal rate (MRR). The artificial neural network (ANN) model has been developed for MRR and finally a hybrid approach of ANN and genetic algorithm has been applied for single objective optimization of MRR.

Keywords: Artificial neural network, EDM, genetic algorithm, material removal rate, optimization