Desirability Function and GA-PSO Based Optimization of Electrochemical Discharge Micro-Machining Performances During Micro-channeling on Silicon-wafer Using Mixed Electrolyte

Silicon-wafer (Si-wafer) is a demandable semiconducting material for micro-fluidic application. Micro-channel on Si-wafer can be produced by electro-chemical discharge micro-machining process (µ-ECDM).Parametric effects on machining depth (MD), overcut (OC) and material removal rate (MRR) has been propounded using mixed electrolyte (NaOH and KOH) varying applied voltage(V), inter electrode gap(IEG)(mm),electrolyte concentration(wt%), pulse on time (µs) and duty ratio (%)during micro-channel cutting on Silicon-wafer using tungsten carbide(WC) cylindrical tool along with X-Y-Z axis movement by computer aided sub-system. ANOVA has been analysed to test adequacy of developed mathematical models and multi criteria parametric optimization and comparative analysis has been performed to interpretation maximum machining depth with higher material removal at lower overcut using desirability function analysis based on Response Surface Methodology (RSM), Genetic Algorithm (GA) and Particle swarm optimization (PSO).The SEM analysis has been made to find-out debris and to clear the micro-channel quality of Si-wafer. It is found that multi-response optimization parametric combinations are 50 V/55µs/31mm IEG/0.45 duty ratio/26.66wt% of NaOH and KOH mixed electrolyte. Particle swarm optimization (PSO) provides the best suitable convergence for the micro-machining of Silicon-wafer by ECDM process.