Application of Taguchi and Response Surface Methodology (RSM) in Steel Turning Process to Improve Surface Roughness and Material Removal Rate

This study investigates the turning process parameters on EN31 steel. The input parameters considered for the study are cutting speed (S), feed (F) and depth of cut (d). Surface roughness (Ra) and material removal rate (MRR) are considered as the response variables. The statistical planning of the experiment is done by using Taguchi and response surface methodology (RSM). The results indicated that the cutting speed has more significant effect on surface roughness and the depth of cut and feed rate has more significant effect on MRR. The mathematical models are developed for the prediction of responses using Taguchi method and RSM. The R-2 value for the mathematical model developed by Taguchi method for surface roughness and MRR is 97 % and 99 % respectively which indicated the statistical adequacy of the model. The models are validated and its found that it predicted the surface roughness and MRR with less than 6 % of error. (C) 2018 Elsevier Ltd. All rights reserved. Selection and/or Peer-review under responsibility of International Conference on Advances in Materials and Manufacturing Applications [IConAMMA 2017].