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

  • R. Ramanujam
    ,
  • Lohithaksha Maiyar
    ,
  • K. Venkatesan
    ,
  • Mithun Vasan
Research Output: Contribution to journal Article Peer-review

Open access

Abstract

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).

Publication Information

Output type

Research Output: Contribution to journal Article Peer-review

Original language

English

Pages from-to (Number of pages)

Pages 457-463

Journal (Volume, Issue Number)

ARPN Journal of Engineering and Applied Sciences (Volume 9, Issue 4)

Publication milestones

  • Published - 01/04/2014

Publication status

Published - 01/04/2014

ISSN

2409-5656

External Publication IDs

  • handle.net: 10547/624666
  • Scopus: 84898974741

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