Abstract
The need for sophisticated material goods has continuously increased in the contemporary era of research and technology. Precision machining of sophisticated materials has long been a source of worry for scientists and academics. In the commercial and industrial sectors, shape memory alloys are a kind of sophisticated material that is becoming more widely employed as time goes on. It is a highly uncommon and distinct substance with the property of resuming its original shape after being subjected to low exact temperature conditions. Because of its shape-recovery design, it is a valuable metal for large-scale industrial applications due to its high strength and durability. SMAs are also divided into three types: those that are reliant on NiTi, those that are based on Cu, and those that are based on Fe. The Fe-based alloy has a high elasticity and damping coefficient, as well as a broad temperature range. When applying electrical discharge machining on Fe-based SMA, this research aims to examine the effects of pulse-on time, pulse-off time, peak current, and distance voltage on surface roughness and dimensional deviation. 11.26 and 4.18 m were the highest and lowest levels of surface roughness measured. The dimensional variation ranges from a minimum of 0.02 to a maximum of 0.21 mm. When it comes to surface roughness, the amount of peak current and the timing of the pulse are more important factors. SEM micrographs of the workpiece show the development of microcracks, craters, pockmarks, pores, extruded material, globules of debris, recast layer, macro-ridges, and other features on the surface of the workpiece sample after EDM operations. The variation in the size of the workpiece samples following EDM operations on Fe-based SMA samples was shown in SEM micrographs.
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Singh, R., Singh, R.P., Trehan, R. (2023). Parametric Study of Process Parameters on Surface Roughness and Dimensional Deviation in Electrical Discharge Machining of Fe-Based SMA. In: Singh, R.P., Tyagi, M., Walia, R.S., Davim, J.P. (eds) Advances in Modelling and Optimization of Manufacturing and Industrial Systems. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-19-6107-6_2
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DOI: https://doi.org/10.1007/978-981-19-6107-6_2
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