A Review: Influence of electrode geometry and process parameters on surface quality and MRR in EDM using Artificial Neural Network

摘要

Electrical Discharge Machining (EDM) is a non conventional machining process, where electrically conductive materials are machined by using precisely controlled sparks that occur between an electrode and a work piece in the presence of a dielectric fluid. It has been a demanding research area to model and optimize the EDM process in the present scenario. Lots of efforts have been exercised to model and optimize the performance and process parameters of EDM process using ANN. To model ANN architectures, learning/training algorithms and nos. of hidden neurons are varied to accomplish minimum error, but the deviation is made in an arbitrary manner. Artificial Neural Network model should be generated for both electrode geometry and various electrode materials to compare the influence of both in EDM