期刊
ENGINEERING SCIENCE AND TECHNOLOGY-AN INTERNATIONAL JOURNAL-JESTECH
卷 20, 期 3, 页码 1220-1226出版社
ELSEVIER - DIVISION REED ELSEVIER INDIA PVT LTD
DOI: 10.1016/j.jestch.2016.10.019
关键词
ANN; Brass; Cutting forces; Regression; Turning
The life of a cutting tool is greatly influenced by the forces acting on it during a cutting operation. A machining operation is a complex process. It is very difficult to develop a comprehensive model involving all the parameters. The present study aims to develop a model to investigate the effects of cutting parameters (speed, depth of cut and feed rate) on the cutting forces during the turning operation of red brass (C23000) using high speed steel (HSS) tool. The experimental results are based on full factorial design methodology to increase the reliability and confidence limit of the data. Artificial neural network and multiple regression approaches were used to model the cutting forces on the basis of cutting parameters. In order to check the adequacy of the regression model, analysis of variance (ANOVA) was used. It was clear from the ANOVA that the regression model is capable to predict the cutting forces with high accuracy. However, ANN model was found to be more accurate than the regression model. (C) 2016 Karabuk University. Publishing services by Elsevier B.V.
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