A hybrid Taguchi based grey relational analysis of hard turning of subzero treated EN24 alloy steel. (2021)

• Record Type: Journal Article
• Authors: Karthikeyan, KMB; Yuvaraj, C.; Balasubramanian, T.
• Is Part Of: Materials today. Volume 46:Part 9(2021)
• Page Start: 3275
• Page End: 3281
• Publication Date: 2021
• Subjects: Dry turning -- Taguchi -- ANOVA -- Grey relational analysis -- Multi-objective optimization; Materials science -- Congresses -- Periodicals; 620.1
• DOI: 10.1016/j.matpr.2020.11.356
• Languages: English
• ISSNs: 2214-7853

Abstract

Abstract: In recent years hard part machining of steels has become a very popular technique replacing grinding operation. The potential benefits such as surface finish, higher material removal rate, enhanced productivity, reduced or consolidated energy consumption, and eco-friendly machining offers dry or hard part turning as an effective replacement for the cylindrical grinding of steels. An attempt has been made to enhance the material hardness by cryo-treating the EN24 steel followed by dry turning. The effect of dry turning over the process response characteristics like surface roughness and cutting force on the EN24 alloy steel was evaluated using Taguchi based grey relational analysis. A Taguchi L9 orthogonal array was designed and nine experimental runs were conducted based on the designed experiments. The process response characteristics are studied and correlated using the grey relational multi-objective optimization approach and analyzed for the influential input parameters on the response characteristics. Based on the results of verification experiments, it is suggested that the hybrid Taguchi based grey relational analysis can be effectively used to find the optimal influential input parameters for the hard or dry turning of subzero treated EN24 alloy steel.