OPTIMIZATION OF MACHINING CHARACTERISTICS OF TITANIUM-BASED BIOMATERIALS: APPROACH TO OPTIMIZE SURFACE INTEGRITY FOR IMPLANTS APPLICATIONS

Abstract

Nowadays, there has been continuous development of metallic biomaterials to meet special needs in the manufacturing of biomedical implants, units and systems so as to function well in the required environment. Developed biomaterials which possess exceptional properties in terms of biocompatibility and biomechanical compatibility require precision processing and machining to obtain the desired dimensional tolerances. Electrical discharge machining (EDM) is the noncontact or nontraditional process of machining that suits the precision machining of biomaterials. In this work, an effort was made to optimize the EDM parameters during machining of titanium-based biomaterials Ti-6AL-4V, so that the multi-objective responses could be obtained. The response surface method was used in designing the experiment, while the grey relational method was used to analyze the effect of multiple objectives into a single unit. The electrical parameters that were considered in this study include peak current, gap voltage, pulse turn-on and duty cycle. These parameters were set within the acceptable limits of the equipment. Three responses were studied, which are tool wear rates (TWRs), material removal rate (MRR) and surface roughness (SR). Using the signal-to-noise ratio and ANOVA optimum tool/electrode wear rate (TWR) is obtained at [Formula: see text][Formula: see text]g/min with process parameters [Formula: see text] A, [Formula: see text][Formula: see text]V, [Formula: see text][Formula: see text][Formula: see text]s, [Formula: see text]%. Optimum values of material removal rate (MRR) are obtained as 0.01035[Formula: see text]g/min with process parameters [Formula: see text] A, [Formula: see text][Formula: see text]V, [Formula: see text][Formula: see text][Formula: see text]s, [Formula: see text]%. Optimum SR is observed as 2.258[Formula: see text][Formula: see text]m with EDM process parameters [Formula: see text] A, [Formula: see text][Formula: see text]V, [Formula: see text][Formula: see text][Formula: see text]s, [Formula: see text]%. Surface characteristics are verified with SEM micrographs. Whereas, grey relation analysis predicted the multi-objective optimum response characteristics. Based on the grey relation grade, experiment number 7 ([Formula: see text][Formula: see text]A, [Formula: see text][Formula: see text]V, [Formula: see text][Formula: see text][Formula: see text]s, [Formula: see text]%) secured the first rank among the experiments/trails.