IJE TRANSACTIONS C: Aspects Vol. 31, No. 6 (June 2018) 1284-1292   

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R. Raju, M. N, M. S. V and L. K. K
( Received: November 07, 2017 – Accepted: March 09, 2018 )

Abstract    Electrical Discharge Machining (EDM) has the capability of machining complicated shapes in electrically conductive materials independent of hardness of the work materials. The need for decision making is increasingly important in the any manufacturing domain because of making high quality products and rapid changes in design. This present article details the development of multiple regression models for envisaging the material removal rate (MRR) and roughness of machined surface in Electrical Discharge Machining (EDM) of Hastelloy C276. The experimental runs are devised as per Taguchi’s principles and empirical relations are established using multiple regression analysis. Taguchi’s methodology can be applied as a single aspects optimization technique for attaining the best set of possible process parameter for material removal rate and roughness of the machined surface. A statistical tool called Analysis of variance (ANOVA) is employed for determining the significance of input process variables that influences the desired performance measures such as material removal rate and roughness of the electrically machined surface. The developed multiple regression models are flexible, competent and precise in prediction of desired performance measures. The developed regression models were validated and the predicted results from the evolved regression models are closer with the experimental outcomes.


Keywords    Electrical Discharge Machining, Taguchiís Design approach, Hastelloy, Analysis of Variance, Regression Analysis.


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