Abstract
This article describes the optimization of processing parameters for the surface roughness of AISI316 austenitic stainless steel. While experimenting, parameters in the process like feed rate (fd), speed (vc), and depth of cut (DoC) were used to study the outcome on the surface roughness (Ra) of the workpiece. The experiment was carried out using the design of experiments (DOE) on a computer numerical control (CNC) lathe. The surface roughness is tested for three conditions i.e. Dry, Wet, and cryogenic conditions after the turning process. Samples are step turned on CNC Lathe for all three conditions with a set of experiments designed. The response surface methodology is implemented, and mathematical models are built for all three conditions. The nature-inspired algorithm is the best way to get the optimal value. For the discussed problem in the paper, nature-inspired techniques are used for obtaining the optimum parameter values to get minimum surface roughness for all set conditions. The Grasshopper optimization algorithm (GOA) is the technique that is the most effective method for real-life applications. In this research, GOA is used to get optimum values for the surface roughness (Ra) at Dry, Wet and cryogenic conditions. Finally, results are compared, and it's observed that the values obtained from GOA are minimum in surface roughness value.
Highlights
Stainless steel is called corrosion resilient steel due to iron-based steel alloy with a least chromium content of 11 %
The measurement was taken at three instants on the machined surface and the average surface roughness value was taken
The optimal values obtained for surface roughness with the help of the signal-to-noise ratio (S/N) ratio was observed that in the dry condition the influencing factor is feed rate, in the wet condition the influencing factor is the depth of cut and in the cryogenic condition the influencing factor is feed rate
Summary
Stainless steel is called corrosion resilient steel due to iron-based steel alloy with a least chromium content of 11 %. As AISI 316 austenitic stainless-steel material needs to be machined, it is necessary to study the influence of machining (turning) on the surface finish and the cutting tool. Youssef Touggui et al [5] studied various parameters affecting material removal rate and surface roughness on AISI 316 in turning operation. The parameters considered were speed, feed and depth of cut in the research study. Studied and presented the cryogenic cooling effect on turning of different metals and alloys. Muhammmad Yasir et al [7] researched on effect of cutting speed and feed rate on surface roughness of AISI 316l. The focus of their study was to find out the effect on surface roughness with respect to different parameters.
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