Plasma arc machining is a well-recognized unconventional machining process widely used to machine intricate part profiles for alloys which are difficult to machine. The surface roughness, material removal rate (MRR), and kerf ratio are predominant factors which influence the performance and quality of plasma cut surfaces. The present research focusses on the effect of plasma arc cutting parameters such as arc voltage, cutting speed, standoff distance, and plasma offset on the cut quality characteristics of SS 304 alloy machined using two different types of nozzles (130 A and 200 A). The experiments were conducted according to a mixed Taguchi design of L18 orthogonal array, and grey relational analysis technique is used for optimization of the above-said cutting conditions. The experimentation on SS 304 alloy is carried out using two different nozzles and identified the best suited nozzle to cut SS 304 alloy of thickness 6 mm which produces better surface roughness and MRR characteristics. Scanning electron microscopy analysis is carried out to inspect the surface morphologies at various cutting conditions.
Plasma arc machining (PAM) is a non-traditional machining process widely used to machine intricate part profiles for alloys that are difficult to machine. The Burr height, Kerf ratio, and material removal rate (MRR) are predominant factors that influences the performance and quality of plasma cut surfaces. Present research focusses on the effect of plasma arc cutting (PAC) parameters such as gases used, cutting speed, current, arc voltage, and gas pressure on the cut quality characteristics of Inconel 625 alloy. The design of experiments (DOE) technique is used to develop a Taguchi design consisting of L18 orthogonal array. The Grey relational analysis technique is used for optimization of the above said cutting conditions. Finally, the most suitable gas to machine is selected along with the optimal PAM parameters for cutting the Inconel 625 alloy. Scanning electron microscope (SEM) analysis is carried out to inspect the surface morphologies at various cutting conditions.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.