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This research work investigates the influence of process parameters e.g. feed rate and milling layer depth with tool rotation on various performance criteria e.g. overcut, machining depth, perpendicularity, radius of curvature of the side wall and surface roughness during electrochemical (EC) milling of Ti6Al4V with the indigenously developed setup. In this study, three most accepted multicriteria and decision-making (MCDM) techniques e.g. SAW, TOPSIS and MOORA are utilized for finding out the optimal parametric combination followed by fabrication of different three-dimensional complex features on Ti6Al4V at that optimal parametric combination. This study confirms that internal flushing with tool rotation improves the accuracy of the machined profile due to better removal of sludge from the machining zone. Developed milling setup is able to generate different complex and three- dimensional features on Ti6Al4V with desired accuracy. Using 1M of NaNO₃ and NaCl mixed electrolyte, at 4.4mm/min of feed rate and 0.25mm of milling layer depth with tool rotation, best values of width overcut, average depth, side angle, radius of curvature and surface roughness ($R_a)$ are achieved as 0.666mm, 1.538mm, 47^∘, 2.091mm, and 1.462$\mu$m, respectively.

The production of miniature parts by the electrochemical discharge micromachining process ($\mu$-ECDM) draws the most of attractions into the industrial field. Parametric influences on machining depth (MD), material removal rate (MRR), and overcut (OC) have been propounded using a mixed electrolyte (NaOH:KOH- 1:1) varying concentrations (wt.%), applied voltage ($V$), pulse on time ($\mu$s), and stand-off distance (SOD) during microchannel cutting on silica glass (SiO${}_2+{\mathrm{\text{NaSiO}}}_3$). Analysis of variances has been analyzed to test the adequacy of the developed mathematical model and multiresponse optimization has been performed to find out maximum MD with higher material removal at lower OC using desirability function analysis as well as neural network (NN)-based Particle Swarm Optimization (PSO). The SEM analysis has been done to find unexpected debris. MD has been improved with better surface quality using a mixed electrolyte at straight polarity using a tungsten carbide (WC) cylindrical tool along with $X$, $Y$, and $Z$ axis movement by computer-aided subsystem and combining with the automated spring feed mechanism. PSO-ANN provides better parametric optimization results for micromachining by the ECDM process.

Highly ordered anodic aluminum oxide (AAO) membranes with pore interval from 100nm to 520nm were fabricated successfully in the mixed electrolytes, which are composed of 0.3M oxalic acid and 1wt.% phosphoric acid/0.01M aluminum oxalate. The study results show that oxalic acid volume percentage has an approximate linear relationship with the optimal anodic oxidation voltage. The optimal anodic oxidation voltage is basically equal to the critical oxidation voltage. The theoretical analysis suggests that the anodic oxidation current is closely related to the ionization constants of acid radical ion in the electrolyte. Since the secondary ionization constant of oxalic radical ion is greater than that of phosphoric acid radical ion, the optimal anodic oxidation voltage increases and the steady anodic oxidation current decreases with the decrease of oxalic acid volume percent.