Optimization in Turning of Ti-6AL-4V Using Anova and Regression Analysis

Abstract

Surface roughness is an important factor to evaluate cutting performance. The primary factors such as speed, feed, depth of cut, type of material, tool geometry etc. have high impact on surface roughness. So it is a measure of product quality since it greatly influences the performance of mechanical parts as well as production cost. This paper developed a regression model and carried out Analysis of variance (ANOVA) to investigate the machining parameters such as cutting speed, feed rate, depth of cut and nose radius, affecting the roughness of surface produced in wet turning process of Ti-6Al-4V work material using CVD coated carbide inserts. The experiment has been designed and carried out on the basis of a three level, Taguchi’s 27 Orthogonal Array ((OA) design.

Authors and Affiliations

V G Aswathy, Dr. N. Rajeev

Keywords

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  • EP ID EP21288
  • DOI -
  • Views 292
  • Downloads 5

How To Cite

V G Aswathy, Dr. N. Rajeev (2015). Optimization in Turning of Ti-6AL-4V Using Anova and Regression Analysis. International Journal for Research in Applied Science and Engineering Technology (IJRASET), 3(9), -. https://europub.co.uk/articles/-A-21288