International Journal of Advanced Mechanical Engineering. ISSN 2250-3234 Volume 4, Number 6 (2014), pp. 667-674 © Research India Publications http://www.ripublication.com Prediction of Surface Roughness in WEDM Process Using Feed Forward Back Propagation Neural Network Piyush Pant 1 , Navneet k Pandey 2 , S.Rajesha 3 and Gaurav Jain 4 1 M.Tech Research Scholar, JSSATE Noida, Uttar Pradesh 1, 2, 3 ME Deptt, JSSATE, Uttar Pradesh ABSTRACT The surface roughness quality significantly influences the machined parts during their useful life. It is very hard to develop a comprehensive model involving all the input parameters because of the complexity of the machining process. In the present study, surface roughness is measured during wire cut electrical discharge machining (WEDM) process for different values of pulse- on time, gap voltage and wire feed rate using L27 OA. Artificial neural network is used to model the surface roughness which is trained and validated using feed forward back propagation method, Levenberg-Marquardt (LM) training algorithm, tansig transfer function using one hidden layer, four neurons and 1000 epochs were carried out. The LM model has produced absolute fraction of variance (R 2 ) values of 0.98069 for the training data, 0.99906 for validation and overall to be 0.96721. The mean square error decreased from 0.005 to 0.000005 during ANN training. The predicted ANN data was well within the limits and the simulation also showed good accuracy. The results indicated that well trained neural network model is quite effective for prediction of surface roughness within and beyond the experimental domain. Keywords: Surface roughness, Wire electrical discharge machining, Artificial neural network. INTRODUCTION WEDM is a non-conventional precision machining process that is widely used in tool and dies making industry. The machining principle is based on erosion of the work- piece material using a successive discrete discharges occurring between the wire electrode and workpiece. Die-making industry is very important to down-stream industries and any technological changes in the die-making industry surely affect