Machining performance of titanium based prosthetic alloy: a grey relational approach

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ABSTRACT

Machining performance of extruded Ti-6Al-4 V prosthetic alloy was investigated through

electrical discharge machining (EDM) using copper as electrode material. Experimental sequencing followed the Box-Behnken design (BBD) of response surface methodology (RSM). Effects of pulse current (Ip), gap voltage (Vg) and pulse-on time (Ton) on material removal rate (MRR), electrode wear rate (EWR) and average surface roughness (Ra) were studied during the process. Increase of MRR and Ra was noticed on increasing any of the considered machining parameters. EWR increased on increasing Ip and Ton, but it reduced with increase of Vg. Regression models were developed and significance of machining parameters was highlighted through analysis of variance (ANOVA). Finally, Taguchi embedded grey relational analysis (GRA) was employed to optimise the responses simultaneously, which resulted the combination of 15 A of pulse current, 30 V of gap voltage and 100 µs of pulse-on time was the optimal parametric combination for the multiple responses.

KEYWORDS:

• Electrical discharge machining
• electrode wear rate
• grey relational analysis
• material removal rate
• prosthetic alloy
• surface roughness

Acknowledgments

Authors are thankful to KIIT Deemed to be University, Bhubaneswar for providing laboratory facility to carry out the experiments.

Disclosure statement

No potential conflict of interest was reported by the author(s).