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...
Main Authors: | , |
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Format: | Article |
Language: | English |
Published: |
Eastern Macedonia and Thrace Institute of Technology
2010-01-01
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Series: | Journal of Engineering Science and Technology Review |
Subjects: | |
Online Access: | http://www.jestr.org/downloads/volume3/fulltext162010.pdf |
Summary: | 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 |
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ISSN: | 1791-2377 |