Parameter optimization of AISI 316 austenitic stainless steel for surface roughness by Grasshopper optimization algorithm

• Published in: Journal of Mechanical Engineering Automation and Control Systems Vol. 2; no. 2; pp. 87 - 97
• Main Authors: Jawade, Samidha, Kulkarni, Omkar K., Kakandikar, G. M.
• Format: Journal Article
• Language: English
• Published: 31.12.2021
• ISSN: 2669-2600; 2669-1361; 2669-1361
• DOI: 10.21595/jmeacs.2021.22149

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.