The current social and industrial communities exceedingly demanded the materials that dealt with rich mechanical properties, i.e., the rich strength, hardness, reliability, high resistance against corrosion and oxidation, and high toughness and refractoriness. Recently, the researchers ascertained the comprehensive applications of these difficult to machine materials in the domain of automotive, aeronautical, nuclear industries etc. It is claimed that it is quite hard and expensive for machining these superadvanced materials by traditional machining operations. In the present study, worldwide promising nickel-based superalloy Inconel 825 material is used due to its outstanding mechanical and thermal properties at eminent temperatures and also having broad application in imperative engineering fields. The authors probed that machining cost and smart machinability index have become the gigantic concern in EDM operation; however, these can be minimized by adapting a conduit of evaluation of the optimum setting among multiple input parameters. It was a challenging task, which is respected by authors as the research gaps to be sorted out. To fulfill research gaps, the authors encountered imperative significant EDM input parameters, i.e., spark gap (Sg), gap voltage (Vg), pulse on time (Ton), pulse off time (Toff), Peak Current (Ip), Servo feed (Sf), Depth of Cut (Dc) and difficulty index (Di) corresponding to output responses, i.e., power consumption (Pc), machining time (Mt), and material removal rate (MRR) for framing the machinability index/model for conducting experiments and collecting objectives/responses/outputs. Next, the authors conducted experiments using the Taguchi L27 orthogonal array model in the nonvibratory domain for recording output responses. Later, to potentially access the results, the authors integrated the computational Taguchi methodology with dual models which is called as Taguchi-grey relational analysis (T-GRA) and Taguchi-principal component analysis (T-PCA). The optimum setting condition among considered inputs is discussed in the conclusion section. Later, confirmatory test gratified the evaluated optimum settings which is yielding an improvement of 0.16262 and 0.34398 score in executing T-GRA and T-PCA, respectively. In continuation, the current research evidenced that pulse off time is the chief significant process parameter having
p
values 0.005 and 0.001 for T-GRA and T-PCA, respectively. It is also seen that the depth of cut is also another important significant process parameter having
p
values 0.061 and 0.073 for T-GRA and T-PCA, respectively. Moreover, the current research work also investigated the effect of variation of momentous input process parameters over the surface topography and their utility in improving surface integrity and eliminating the micropores and cracks.
