%0 Journal Article
%T Relevance Vector Machine Based Analyses of MRR and SR of Electrodischarge Machining Designed by Response Surface Methodology
%A Kanhu Charan Nayak
%A Rajesh Kumar Tripathy
%A Sudha Rani Panda
%J International Journal of Manufacturing Engineering
%D 2013
%R 10.1155/2013/170746
%X Relevance vector machine is found to be one of the best predictive models in the area of pattern recognition and machine learning. The important performance parameters such as the material removal rate (MRR) and surface roughness (SR) are influenced by various machining parameters, namely, discharge current ( ), pulse on time ( ), and duty cycle (tau) in the electrodischarge machining process (EDM). In this communication, the MRR and SR of EN19 tool steel have been predicted using RVM model and the analysis of variance (ANOVA) results were performed by implementing response surface methodology (RSM). The number of input parameters used for the RVM model is discharge current ( ), pulse on time ( ), and duty cycle (tau). At the output, the corresponding model predicts both MRR and SR. The performance of the model is determined by regression test error which can be obtained by comparing both predicted MRR and SR from model and experimental data is designed using central composite design (CCD) based RSM. Our result shows that the regression error is minimized by using cubic kernel function based RVM model and the discharge current is found to be one of the most significant machining parameters for MRR and SR from ANOVA. 1. Introduction Electrodischarge machining (EDM) has tremendous potentials on account of its versatile application in industry. The applications are like high precision machining of all types of electrical conductors and hard material such as metal and metal alloys like tool steel and steels used for die making in metal forming processes and manufacturing of molds, automotive, aerospace, and surgical components. It has enormous advantages without any physical contact between tool and work piece. This nonconventional machining process uses the thermoelectric energy for machining and removes the material by thermal erosion process. The EDM process involves finite discrete periodic electric sparks created by the electric pulse generator at short intervals between the tool electrode (anode) and work electrode (cathode) separated by a thin film of dielectric liquid that causes the material removal in motion and vaporize form, and these tiny molten vaporize particles are flushed away from the gap by continuous flushing of dielectric liquid. This machining process provides productive with increasing strength of the work material and maintains desire shape, accuracy, and surface integrity requirements [1]. Material removal rate (MRR) and surface roughness (SR) are the most important responses which are influenced by EDM parameters such as voltage
%U http://www.hindawi.com/journals/ijme/2013/170746/