Power Prediction Model for Turning EN-31 Steel Using Response Surface Methodology

Power consumption in turning EN-31 steel (a material that is most extensively used in automotive industry) with tungstencarbide tool under different cutting conditions was experimentally investigated. The experimental runs were planned accordingto 24+8 added centre point factorial design of experime...

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Main Authors: M. Hameedullah, L. B. Abhang
Format: Article
Language:English
Published: Eastern Macedonia and Thrace Institute of Technology 2010-01-01
Series:Journal of Engineering Science and Technology Review
Subjects:
Online Access:http://www.jestr.org/downloads/volume3/fulltext162010.pdf
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spelling doaj-0afc04b0b41d4f5e9a7a2cae32ef83582020-11-24T21:27:25ZengEastern Macedonia and Thrace Institute of TechnologyJournal of Engineering Science and Technology Review1791-23772010-01-0131116122Power Prediction Model for Turning EN-31 Steel Using Response Surface MethodologyM. HameedullahL. B. AbhangPower consumption in turning EN-31 steel (a material that is most extensively used in automotive industry) with tungstencarbide tool under different cutting conditions was experimentally investigated. The experimental runs were planned accordingto 24+8 added centre point factorial design of experiments, replicated thrice. The data collected was statisticallyanalyzed using Analysis of Variance technique and first order and second order power consumption prediction models weredeveloped by using response surface methodology (RSM). It is concluded that second-order model is more accurate than thefirst-order model and fit well with the experimental data. The model can be used in the automotive industries for decidingthe cutting parameters for minimum power consumption and hence maximum productivityhttp://www.jestr.org/downloads/volume3/fulltext162010.pdfPowerResponse Surface methodologyMatlabMinitabMetal cutting
collection DOAJ
language English
format Article
sources DOAJ
author M. Hameedullah
L. B. Abhang
spellingShingle M. Hameedullah
L. B. Abhang
Power Prediction Model for Turning EN-31 Steel Using Response Surface Methodology
Journal of Engineering Science and Technology Review
Power
Response Surface methodology
Matlab
Minitab
Metal cutting
author_facet M. Hameedullah
L. B. Abhang
author_sort M. Hameedullah
title Power Prediction Model for Turning EN-31 Steel Using Response Surface Methodology
title_short Power Prediction Model for Turning EN-31 Steel Using Response Surface Methodology
title_full Power Prediction Model for Turning EN-31 Steel Using Response Surface Methodology
title_fullStr Power Prediction Model for Turning EN-31 Steel Using Response Surface Methodology
title_full_unstemmed Power Prediction Model for Turning EN-31 Steel Using Response Surface Methodology
title_sort power prediction model for turning en-31 steel using response surface methodology
publisher Eastern Macedonia and Thrace Institute of Technology
series Journal of Engineering Science and Technology Review
issn 1791-2377
publishDate 2010-01-01
description Power consumption in turning EN-31 steel (a material that is most extensively used in automotive industry) with tungstencarbide tool under different cutting conditions was experimentally investigated. The experimental runs were planned accordingto 24+8 added centre point factorial design of experiments, replicated thrice. The data collected was statisticallyanalyzed using Analysis of Variance technique and first order and second order power consumption prediction models weredeveloped by using response surface methodology (RSM). It is concluded that second-order model is more accurate than thefirst-order model and fit well with the experimental data. The model can be used in the automotive industries for decidingthe cutting parameters for minimum power consumption and hence maximum productivity
topic Power
Response Surface methodology
Matlab
Minitab
Metal cutting
url http://www.jestr.org/downloads/volume3/fulltext162010.pdf
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AT lbabhang powerpredictionmodelforturningen31steelusingresponsesurfacemethodology
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