Exploring wide-parametric range for tool electrode selection based on surface characterization and machining rate employing powder-mixed electric discharge machining process for Ti6Al4V ELI

Abstract

The titanium alloy Ti6Al4V ELI (grade 23) is widely used in biomedical industry because of its engineering attributes. However, it requires surface modifications and has processing challenges because it is difficult to machine nature. Therefore, powder-mixed electric discharge machining process is commonly applied to simultaneously machine the material and carry out surface treatment. The performance of the process is limited by both low cutting efficiency and the formation of a rough surface. In this regard, the current study evaluates SiC powder-mixed electric discharge machining of Ti6Al4V ELI using a range of tool materials such as copper, brass, graphite, and aluminum along with a comprehensive list of process parameters. The surface roughness parameters involving arithmetic roughness, the average peak-to-valley distance, and the highest peak-to-deepest valley distance along with material removal rate are comprehensively studied. Taguchi design of experiments L16 orthogonal array is used to study the process performance with parametric effect analysis, parametric significance analysis, and surface morphological analysis with a scanning electron microscope. Furthermore, the experimental results are optimized against a multi-response optimization matrix using grey relational analysis approach. An optimal compromise between surface attributes and cutting efficiency is identified by Al electrode, pulse current of 14 A, pulse on time of 75 µs, pulse off time of 75 µs, and negative polarity parametric conditions.