• Multi-response optimization using anova and desirability function analysis: a case study in end milling of inconel alloy

      Ramanujam, R.; Maiyar, Lohithaksha M.; Venkatesan, K.; Vasan, Mithun; VIT University (Asian Research Publishing Network, 2014-04-01)
      Nickel-based super alloys are classified as 'difficult to machine' materials due to its inherent characteristics such as high hardness, and toughness, high strength at elevated temperatures, low thermal conductivity, ability to react with cutting inserts, and ability to weld onto the surface of the cutting insert. The present study investigated the parameter optimization of end milling operation for Inconel 718 super alloy with multi-response criteria based on the Taguchi method and desirability function analysis. Experimental tests were carried out based on an L9 orthogonal array of Taguchi method. The influence of machining factors cutting speed, feed rate and depth of cut were analyzed on the performances of surface roughness and material removal rate. The optimum cutting conditions are obtained by Taguchi method and desirability function. The analysis of variance (ANOVA) is also applied to investigate the effect of influential parameters. A regression model was developed for surface roughness and material removal rate as a function of cutting velocity, feed rate and depth of cut. Finally, the confirmation experiment was conducted for the optimal machining parameters, and the betterment has been proved. © 2006-2014 Asian Research Publishing Network (ARPN).
    • Optimization of machining parameters for end milling of Inconel 718 super alloy using Taguchi based grey relational analysis

      Maiyar, Lohithaksha M.; Ramanujam, R.; Venkatesan, K.; Jerald, J.; VIT University; National Institute of Technology, India (Elsevier Ltd, 2013-11-13)
      This study investigated the parameter optimization of end milling operation for Inconel 718 super alloy with multi-response criteria based on the taguchi orthogonal array with the grey relational analysis. Nine experimental runs based on an L9 orthogonal array of Taguchi method were performed. Cutting speed, feed rate and depth of cut are optimized with considerations of multiple performance characteristics namely surface roughness and material removal rate. A grey relational grade obtained from the grey relational analysis is used to solve the end milling process with the multiple performance characteristics. Additionally, the analysis of variance (ANOVA) is also applied to identify the most significant factor. Finally, confirmation tests were performed to make a comparison between the experimental results and developed model. Experimental results have shown that machining performance in the end milling process can be improved effectively through this approach.