Abstract




 
   

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

downloaded Downloaded: 0   viewed Viewed: 114

  MATHEMATICAL MODELING AND ANALYSIS OF SPARK EROSION MACHINING PARAMETERS OF HASTELLOY C-276 USING MULTIPLE REGRESSION ANALYSIS (TECHNICAL NOTE)
 
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.

 

References    Cai, X., Qin, S., Li, J., An, Q. and Chen, M., “Experimental investigation on surface integrity of end milling nickel based alloy - Inconel 718”, Machining Science and Technology: An International Journal. Vol. 18, (2014), 31-46.Wu, Q., “Serrated chip formation and tool-edge wear in high-speed machining of advanced aerospace materials”, Utah State University, Logan, Utah, (2007).Pervaiz, S., Rashid, A., Deiab, I. and Nicolescu, M., “Influence of tool materials on machinability of titanium- and nickel-based alloys: A Review”, Materials and manufacturing processes, Vol. 29, (2014), 219-252.Kuppan, P., Narayanan, S., Rajadurai, A. and Adithan, M., “Effect of EDM parameters on hole quality characteristics in deep hole drilling of Inconel 718 superalloy”, International Journal of Manufacturing Research, Vol. 10, No. 1, (2015), 45-63.Qu, N. S., Hu, Y., Zhu, D. and Xu, Z. Y., “Electrochemical machining of blisk channels with progressive pressure electrolyte flow”, Materials and manufacturing processes. Vol. 29, (2014), 572-578.Ho, K. H. and Newman, S. T., “State of the art electrical discharge machining (EDM)”, International Journal of  Machine Tools and Manufacture, Vol. 43, (2003), 1287 – 1300.Moghaddam, M. A. and Kolahan, F., “Improvement of surface finish when EDM AISI 2312 hot worked steel using Taguchi approach and genetic algorithm”, International Journal of Engineering-Transactions C: Aspects, Vol. 27, No. 3 (2014), 417-424.Moghaddam, M.A. and Kolahan, F., "Optimization of EDM process parameters using statistical analysis and simulated annealing algorithm", International Journal of Engineering-Transactions A: Basics, Vol. 28, No. 1, (2015), 154-161.El-Hofy, H., “Advanced machining processes”, McGraw-Hill, New York, (2005).Kuppan, P., Rajadurai, A. and Narayanan, S., “Influence of EDM process parameters in deep hole drilling of Inconel 718”, International Journal of Advanced Manufacturing Technology, Vol. 38, (2008), 74–84.Dhanabalan, S., Sivakumar, K. and Narayanan, C. S., “Optimization of machining parameters of EDM while machining Inconel 718 for form tolerance and orientation Tolerance”, Indian Journal of Engineering and Materials Sciences, Vol. 20, (2013), 391–397.Bharti, P. S, Maheshwari, S. and Sharma, C., “Experimental investigation of Inconel 718 during die- sinking electric discharge machining”, International Journal of Engineering Science and Technology, Vol. 2, (2010), 6464–6473.Caiazzo, F., Cuccaro, L., Fierro, I., Petrone, G. and Alfieri, V., “Electrical discharge machining of René 108 DS nickel superalloy for aerospace turbine blades”, Procedia CIRP, Vol. 33, (2015), 382 – 387.Caydas, U. and Hascalık, A., “A study on surface roughness in abrasive waterjet machining process using artificial neural networks and regression analysis method”, Journal of materials processing technology, Vol. 202, (2008), 574–582.Neshat, N., “An approach of artificial neural networks modeling based on fuzzy regression for forecasting purposes”, " International Journal of Engineering, Transactions B: Applications,  Vol. 28, No. 11 (2015), 1651-1655.Sahoo, A. K. and Pradhan, S., “Modeling and optimization of Al/SiCp MMC machining using Taguchi approach”, Measurement, Vol.46, (2013), 3064–3072. Ahilan, C., Kumanan, S., Sivakumaran, N. and  Dhas, J. E. R., “Modeling and prediction of machining quality in CNC turning process using intelligent hybrid decision making tools”,  Applied Soft Computing,  Vol.13, (2013), 1543–1551.





International Journal of Engineering
E-mail: office@ije.ir
Web Site: http://www.ije.ir