a b s t r a c tThe current work presents a comparative study of wire electrical discharge machining (WEDM) of armour materials such as aluminium alloy 7017 and rolled homogeneous armour (RHA) steel using buckingham pi theorem to model the input variables and thermo-physical characteristics of WEDM on material removal rate (MRR) and surface roughness (Ra) of Al 7017 and RHA steel. The parameters of the model such as pulse-on time, flushing pressure, input power, thermal diffusivity and latent heat of vaporization have been determined through design of experiment methodology. Wear rate of brass wire increases with rise in input energy in machining Al 7017. The dependence of thermo-physical properties and machining variables on mechanism of MRR and Ra has been described by performing scanning electron microscope (SEM) study. The rise in pulse-on time from 0.85ms to 1.25ms causes improvement in MRR and deterioration of surface finish. The machined surface has revealed that craters are found on the machined surface. The propensity of formation of craters increases during WEDM with a higher current and larger pulse-on time.
a b s t r a c tIn the current investigation, a multi response optimization technique based on Taguchi method coupled with Grey relational analysis is planned for wire-EDM operations on ballistic grade aluminium alloy for armour applications. Experiments have been performed with four machining variables: pulse-on time, pulse-off time, peak current and spark voltage. Experimentation has been planned as per Taguchi technique. Three performance characteristics namely material removal rate (MRR), surface roughness (SR) and gap current (GC) have been chosen for this study. Results showed that pulse-on time, peak current and spark voltage were significant variables to Grey relational grade. Variation of performance measures with process variables was modelled by using response surface method. The confirmation tests have also been performed to validate the results obtained by Grey relational analysis and found that great improvement with 6% error is achieved.
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