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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Eastern Macedonia and Thrace Institute of Technology
2010-01-01
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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 |
work_keys_str_mv |
AT mhameedullah powerpredictionmodelforturningen31steelusingresponsesurfacemethodology AT lbabhang powerpredictionmodelforturningen31steelusingresponsesurfacemethodology |
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1725974691088171008 |