Electrical discharge machining of Fe-based shape memory alloy: Parametric evaluation with microstructure analysis

In the real world, shape memory alloys (SMAs) are a great option for industrial applications including orthopedic implacers, micro tools, actuators, fitting and screening components, military appliances, aerospace components, biomedical instruments, fabricating essentials, etc. Despite their remarkable characteristics, the effective production of these alloys continues to be a problem for researchers worldwide. This paper has aimed to examine the considered machining responses, that is, material removal rate (MRR) and surface roughness (SR) in electrical discharge or spark machining (EDM) of Fe-based SMA using a Cu-electrode under varying settings of input factors namely as pulse on time (Ton), pulse off time (Toff), peak current (Ip), and gap voltage (GV). The central composite design matrix has been employed for planning the main runs. The experimental results reflect the lowest and highest for MRR as 12.49 and 73.90 mm(3)/min; and for SR as 5.03 and 6.65 mu m, respectively. The microstructure analysis of the EDMed work samples and tool electrode surfaces has also been conducted using scanning electron microscopy. The micrographs exposed the development of debris, craters, micro-cracks, and recast layer creation on the workpiece surface and electrode tool as well. The creation of debris develops as a result of large spark energy at the work sample-tool contact as a result of a high peak current and long pulse on time. Furthermore, single and multi-objective optimization of investigated responses (i.e. MRR and SR) were tried using the desirability approach, teacher learning-based optimization (TLBO), and particle swarm optimization (PSO) techniques. The obtained optimized values for MRR and SR by using the desirability approach, TLBO, and PSO are 62.69 mm(3)/min and 5.56 mu m; 78.85 mm(3)/min and 4.34 mu m; and 78.91 mm(3)/min and 4.35 mu m, correspondingly.