Multi-Response Optimization of Wire Electrical Discharge Machining for Titanium Grade-5 by Weighted Principal Component Analysis


  • Sachin Ashok Sonawane Research Scholar, Walchand Institute of Technology, Solapur 413006, Maharashtra, India
  • Mahesh Laxmikant Kulkarni Professor, Rajarshi Shahu School of Engineering and Research, Narhe, Pune, Maharashtra, India.


WEDM, titanium grade-5, Taguchi method, weighted principal component analysis, ANOVA, SEM analysis


This paper reports the results of research to examine the effects of cutting parameters such as pulse-on time, pulse-off time, servo voltage, peak current, wire feed rate and cable tension on surface finish, overcut and metal removal rate (MRR) during Wire Electrical Discharge Machining (WEDM) of grade-5 titanium (Ti-6Al-4V). Taguchi’s L27 orthogonal design method is used for experimentation. Multi-response optimization is performed by applying weighted principal component analysis (WPCA). The optimum values of cutting variables are found as a pulse on time 118 µs, pulse off time 45 µs, servo voltage 40 volts, peak current 190 Amp. , wire feed rate 5 m/min and cable tension 5 gram. On the other hand, Analysis of Variance (ANOVA), simulation results indicate that pulse-on time is the primary influencing variable which affects the response characteristics contributing 76.00%. The results of verification experiments show improvement in the value of output characteristics at the optimal cutting variables settings. Scanning electron microscopic (SEM) analysis of the surface after machining indicates the formation of craters, resolidified material, tool material transfer and increase in the thickness of recast layer at higher values of the pulse on time.


E. O. Ezugwu and Z. M. Wang, “Titanium alloys and their machinability-a review,” Journal of Materials Processing Technology, vol. 68, no. 3, pp. 262-274, August 1997.

K. H. Ho, S. T. Newman, and S. Rahimifard, “State of the art in wire electrical discharge machining (WEDM),” International Journal of Machine Tools and Manufacture, vol. 44, no. 12-13, pp. 1247-1259, October 2004.

H. C. Liao, “Multi-response optimization using weighted principal component,” International Journal of Advanced Manufacturing Technology, vol. 27, no. 7-8, pp. 720-725, Febuary 2006.

S. K. Gauri and S. Chakraborty, “Optimization of multiple responses for WEDM processes using weighted principal components,” International Journal of Advanced Manufacturing Technology, vol. 40, no. 11-12, pp. 1102-1110, Febuary 2009.

B. C. Routara, S. D. Mohanty, S. Datta, A. Bandopadhyay, and S. S. Mahapatra, “Combined quality loss concept in WPCA-based Taguchi philosophy for optimization of multiple surface quality characteristics of UNS C34000 brass in cylindrical grinding,” International Journal of Advanced Manufacturing Technology, vol. 51, no. 1-4, pp. 135-143, March 2010.

A. Biswas, S. Bhaumik, G. Mujumdar, S. Datta, and S. S. Mahapatra, “Bead geometry optimization of submerged arc weld: exploration of weighted principal component analysis,” Applied Mechanics and Materials, vol. 110, pp. 790-798, 2012.

P. C. Padhi, S. S. Mahapatra, S. N. Yadav, and D. K. Tripathi, “Optimization of correlated quality characteristics in WEDM process using Taguchi approach coupled with principal component analysis,” Journal of Manufacturing Science and Production, vol. 13, no. 3, pp. 199-208, September 2013.

D. Zhao, Y. Wang, S. Sheng, and Z. Lin, “Multi-objective optimal design of small scale resistance spot welding process with principal component analysis and response surface methodology,” Journal of Intelligent Manufacturing, vol. 25, no. 6, pp. 1335-1348, December 2014.

M. K. Das, K. Kumar, T. K. Barman, and P. Sahoo, “Optimization of surface roughness and MRR in EDM using WPCA,” Procedia Engineering, vol. 64, pp. 446-455, 2013.

T. B. Rao and A. Gopal Krishna, “Simultaneous optimization of multiple performance characteristics in WEDM for machining ZC63/SiCp MMC,” Advances in Manufacturing, vol. 1, no. 3, pp. 265-275, September 2013.

S. K. Gauri and S. Pal, “The principal component analysis (PCA)-based approaches for multi-response optimization: some areas of concerns,” International Journal of Advanced Manufacturing Technology, vol. 70, no. 9-12, pp. 1875-1887, February 2014.

B. O. P. Soepangkat and H. C. Kis Agustin, “Multiple performance characteristics optimization in the WEDM process of SKD61 tool steel using Taguchi method combined with weighted principal component analysis (WPCA),” Applied Mechanics and Materials, vol. 758, pp. 21-27, 2015.

S. D. Mohanty, S. S. Mahapatra, and R. C. Mohanty, “Optimization of multiple surface roughness characteristics of electrical discharge machined D2 steel with the help of a tool produced by rapid prototyping using weighted principal component analysis and Taguchi method,” Imperial Journal of Interdisciplinary Research, vol. 2, no. 11, pp. 920-927, 2016.

A. Panda, A. K. Sahoo, and A. K. Rout, “Investigations on surface quality characteristics with multi-response parametric optimization and correlations,” Alexandria Engineering Journal, vol. 55, no. 2, pp. 1625-1633, June 2016.

N. Lusi, K. Muzaka, and B. O. P. Soepangkat, “Parametric optimization of wire electrical discharge machining process on AISI H13 tool steel using weighted principal component analysis (WPCA) and Taguchi method,” ARPN Journal of Engineering and Applied Sciences, vol. 11, no. 2, pp. 945-951, January 2016.

D. M. D. Costa, G. Belinato, T. C. Brito, A. P. Paiva, J. R. Ferreira, and P. P. Balestrassi, “Weighted principal component analysis combined with Taguchi’s signal-to-noise ratio to the multi objective optimization of dry end milling process: a comparative study,” Journal of the Brazilian Society of Mechanical Sciences and Engineering, vol. 39, no. 5, pp. 1663-1681, May 2017.

A. K. Dhakad and J. Vimal, “Multi response optimization of wire EDM process parameters using Taguchi approach coupled with principal component analysis methodology,” International Journal of Engineering, Science and Technology, vol. 9, no. 2, pp. 61-74, 2017.

A. Nair and S. Kumanan, “Multi performance optimization of abrasive water jet machining of Inconel 617 using WPCA,” Materials and Manufacturing Processes, vol. 32, no. 6, pp. 693-699, December 2017.

N. Sharma, R. Khanna, and R. D. Gupta, “WEDM process variables investigation for HSLA by response surface methodology and genetic algorithm,” Engineering Science and Technology an International Journal, vol. 18, no. 2, pp. 171-177, June 2015.

K. Pearson, “On lines and planes of closest fit RO systems of points in space,” Philosophical Magazine, vol. 2, pp. 559-572, 1901.

H. Hotelling, “Analysis of a complex statistical variable into principal components,” Journal of Educational Psychology, vol. 24, no. 6, pp. 417-441, 1933.




How to Cite

S. A. Sonawane and M. L. Kulkarni, “Multi-Response Optimization of Wire Electrical Discharge Machining for Titanium Grade-5 by Weighted Principal Component Analysis”, Int. j. eng. technol. innov., vol. 8, no. 2, pp. 133–145, Mar. 2018.