Experimental investigation during nano powder added µ-ED milling on nickel-titanium shape memory alloy

Abstract

Nickel-titanium (NiTi) shape memory alloy (SMA) is one of the smart materials which has a vast application in the aerospace and biomedical industry due to its shape memory effect (SME), strong corrosion and wear resistance. Thus, the present study investigates the influence of process variables like gap voltage (V), powder concentration (PC) and pulse on time (ton) towards the material removal rate (MRR), surface roughness (SR) and micro-hardness (MH) amid graphene nano powder added micro-electrical discharge milling (µ-ED milling) of NiTi SMA. ANOVA analysis has been carried out to determine the % distribution of individual machining parameters towards all responses. The addition of graphene nano particles to the dielectric oil considerably enhanced the MRR, MH, and decreased the SR of the milled micro-channel. Taguchi’s grey relational analysis (GRA) and grey-desirability approach have been applied for multi-response optimisation to find the maximum MRR, MH, and minimum SR. It is discovered that the grey-desirability method improves all the responses. The Field emission scanning electron microscopy (FESEM) micro-graphs confirm defect-free mirror-like surface finish at the optimal grey-desirability setting. The X-ray diffraction (XRD) analysis discovered the formation of oxides and hardened phases in the machined surface. The application of graphene enhanced the recast layer thickness and reduced the indentation depth at subsurface region. The nano indentation test validates the rise in nano hardness and elastic modulus at the grey desirability optimal setting compared to the initial machining condition.