Prediction of Surface Roughness on Electrical Discharge Machined Surfaces

Abstract

Accurate prediction of surface roughness generating capabilities of manufacturing process is a prerequisite to enhance their uses in areas such as surface texturing. Textured surfaces have numerous applications in various industries such as Automotive, Aerospace, Energy, and Defence. Electrical discharge machining (EDM) process can be used for surface texturing of conductive materials, particularly hard surfaces. A two-step approach is used in this work to develop a mathematical model to predict the roughness of surfaces created by the EDM process based on three input process parameters, namely the spark on time, current, and voltage. Finite Element method is used in the first step to generate a single crater formed by an individual spark. In the subsequent step, online process monitoring is used to capture the random nature of spark generation in the EDM machining process. A surface is generated virtually using this data, resembling the machined surface created by multi-spark EDM with the appropriate spatial distribution. The surface textures obtained from the study were validated with the experimental data. It was found that the measured Surface roughness values at different locations of the textured area of the specimen were within the range predicted by the simulations.