Parametric Optimization of Rotary Ultrasonic Drilling using Grey Relational Analysis

The present article targets to investigate the effects of machining variables on the performance of rotary ultrasonic machining of BK-7 glass and concurrent optimization of output measures through Grey relational analysis. Taguchi approach has been employed for framing the experimental matrix. Machining variables - Feed rate, tool rotational speed and ultrasonic power - have been picked after pilot experimentation to investigate their influence on output measures namely - material removal rate and surface roughness. Thereafter, experimental data was tested using "analysis of variance" for recognizing the significant factors and their relative percentage contribution on the output measures. Then Taguchi approach was integrated with Grey relational analysis for individual as well as concurrent optimization of performance attributes. Feed was found to influence the MRR and SR on a large scale followed by tool rotation speed that has a substantial impact on SR. All the predicted optimal settings were found to be well tuned with experimental results. (C) 2019 Elsevier Ltd. All rights reserved.