Application of Taguchi and regression analysis on surface roughness in machining hardened AISI D2 steel

The objective of the study is to assess the performance of multilayer coated carbide insert in the machining of hardened AISI D2 steel (53 HRC) using Taguchi design of experiment. The experiment was designed based on Taguchi L27 orthogonal array to predict surface roughness. The S/N ratio and optimu...

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Bibliographic Details
Main Author: Ashok Kumar Sahoo
Format: Article
Language:English
Published: Growing Science 2014-04-01
Series:International Journal of Industrial Engineering Computations
Subjects:
Online Access:http://www.growingscience.com/ijiec/Vol5/IJIEC_2013_49.pdf
Description
Summary:The objective of the study is to assess the performance of multilayer coated carbide insert in the machining of hardened AISI D2 steel (53 HRC) using Taguchi design of experiment. The experiment was designed based on Taguchi L27 orthogonal array to predict surface roughness. The S/N ratio and optimum parametric condition are analysed. The analysis of variance has also been carried out to predict the significant factors affecting surface roughness. Based on Taguchi S/N ratio and ANOVA, feed is the most influencing parameter for surface roughness followed by cutting speed whereas depth of cut has least significant from the experiments. In regression model, the value of R2 being 0.98 indicates that 98 % of the total variations are explained by the model. It indicates that the developed model can be effectively used to predict the surface roughness on the machining of D2 steel with 95% confidence intervals.
ISSN:1923-2926
1923-2934