Evaluating of surface morphology on EDD machining parameters for Si3N4-TiN using TLBO-MRA

In this study, electrical discharge drilling (EDD) investigation of Si3N4-TiN ceramic composites is carried out. 25 experimental trials were performed by process parameters and performance characteristics using brass electrode were investigated. Multiple regression analysis (MRA) is employed to develop predictive models, and the validated findings show an accuracy of 90%. An integrated teaching learning based optimization (TLBO) and MRA is employed for simultaneous optimization of all responses. The outcomes were achieved with I = 7.0 A, Pon = 17.6 mu s, Poff = 5 mu s, DP = 17 kg/cm2, S = 5.0 m/sec, MRR = 0.1972 g/min, SR = 0.5194 mu m, WR = 2.5371%, and MT = 0.3018 min. The validated result shows an error of 0.85%, 4.5%, 0.85%, and 4.1% for MRR, SR, MRR, and WR, respectively. Scanning electron micrographs have been proven experimentally, by combining the optimal parameters, to increase machining accuracy, geometrical tolerances, surface quality, and minimize micro-void frequency.