In the current exploration, the machining of a Nimonic 90 superalloy material was carried out in a die-sinking electric discharge machine. Experimentation was performed to investigate the impact of three input machining factors – current (I), pulse on time (Ton) and pulse off time (Toff) – on various response characteristics such as material removal rate (MRR), surface roughness (Ra) and electrode wear rate (EWR).
A Taguchi L9 design and ANOVA were used to assess machine response characteristics. The study also involved a grey relational analysis (GRA) multi-objective technique of optimization.
For single-objective performance, the most appropriate machining factors for achieving the best performance were attained as: MRR (I = 20 A, Ton = 200 µs and Toff = 45 µs), Ra (I = 14 A, Ton = 100 µs and Toff = 25 µs) and EWR (I = 17 A, Ton = 150 µs and Toff = 45 µs). The proposed grey relational approach provided the optimal settings (i.e. 14 A I, 100 µs Ton and 25 µs Toff) for the variables used to calculate the predicted and experimental results. Also, a confirmation test indicated that the final experimental grey relational grade value was enhanced when the experimentation was performed at optimal setting.
To the best of the authors’ knowledge, the present work is the first to examine the proposed machining variables (i.e. current, pulse on time and pulse off time) in relation to the optimization technique of GRA for a Nimonic 90 alloy using a die-sinking electric discharge machining method.
