Prediction of Cutting Force in Turning Process by Using Artificial Neural Network

Cutting forces are important factors for determining machine serviceability and product quality. Factors such as speed feed, depth of cut and tool noise radius affect on surface roughness and cutting forces in turning operation. The artificial neural network model was used to predict cut...

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Autor principal:	Marwa Qasim Ibraheem
Formato:	article
Lenguaje:	EN
Publicado:	Al-Khwarizmi College of Engineering – University of Baghdad 2020
Materias:	Chemical engineering TP155-156 Engineering (General). Civil engineering (General) TA1-2040
Acceso en línea:	https://doaj.org/article/01900d87a745409fbbe1a84df9c77e28
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id	oai:doaj.org-article:01900d87a745409fbbe1a84df9c77e28
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spelling	oai:doaj.org-article:01900d87a745409fbbe1a84df9c77e282021-12-02T10:27:53ZPrediction of Cutting Force in Turning Process by Using Artificial Neural Network10.22153/kej.2020.04.0021818-11712312-0789https://doaj.org/article/01900d87a745409fbbe1a84df9c77e282020-06-01T00:00:00Zhttp://alkej.uobaghdad.edu.iq/index.php/alkej/article/view/674https://doaj.org/toc/1818-1171https://doaj.org/toc/2312-0789 Cutting forces are important factors for determining machine serviceability and product quality. Factors such as speed feed, depth of cut and tool noise radius affect on surface roughness and cutting forces in turning operation. The artificial neural network model was used to predict cutting forces with related to inputs including cutting speed (m/min), feed rate (mm/rev), depth of cut (mm) and work piece hardness (Map). The outputs of the ANN model are the machined cutting force parameters, the neural network showed that all (outputs) of all components of the processing force cutting force FT (N), feed force FA (N) and radial force FR (N) perfect accordance with the experimental data. Twenty-five samples of experimental data were used, including nineteen to train the network. Moreover six other experimental tests were implemented to test the network. The study concludes that ANN was a dependable and precise method for predicting machining parameters in CNC turning operation. Marwa Qasim IbraheemAl-Khwarizmi College of Engineering – University of BaghdadarticleChemical engineeringTP155-156Engineering (General). Civil engineering (General)TA1-2040ENAl-Khawarizmi Engineering Journal, Vol 16, Iss 2 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Chemical engineering TP155-156 Engineering (General). Civil engineering (General) TA1-2040
spellingShingle	Chemical engineering TP155-156 Engineering (General). Civil engineering (General) TA1-2040 Marwa Qasim Ibraheem Prediction of Cutting Force in Turning Process by Using Artificial Neural Network
description	Cutting forces are important factors for determining machine serviceability and product quality. Factors such as speed feed, depth of cut and tool noise radius affect on surface roughness and cutting forces in turning operation. The artificial neural network model was used to predict cutting forces with related to inputs including cutting speed (m/min), feed rate (mm/rev), depth of cut (mm) and work piece hardness (Map). The outputs of the ANN model are the machined cutting force parameters, the neural network showed that all (outputs) of all components of the processing force cutting force FT (N), feed force FA (N) and radial force FR (N) perfect accordance with the experimental data. Twenty-five samples of experimental data were used, including nineteen to train the network. Moreover six other experimental tests were implemented to test the network. The study concludes that ANN was a dependable and precise method for predicting machining parameters in CNC turning operation.
format	article
author	Marwa Qasim Ibraheem
author_facet	Marwa Qasim Ibraheem
author_sort	Marwa Qasim Ibraheem
title	Prediction of Cutting Force in Turning Process by Using Artificial Neural Network
title_short	Prediction of Cutting Force in Turning Process by Using Artificial Neural Network
title_full	Prediction of Cutting Force in Turning Process by Using Artificial Neural Network
title_fullStr	Prediction of Cutting Force in Turning Process by Using Artificial Neural Network
title_full_unstemmed	Prediction of Cutting Force in Turning Process by Using Artificial Neural Network
title_sort	prediction of cutting force in turning process by using artificial neural network
publisher	Al-Khwarizmi College of Engineering – University of Baghdad
publishDate	2020
url	https://doaj.org/article/01900d87a745409fbbe1a84df9c77e28
work_keys_str_mv	AT marwaqasimibraheem predictionofcuttingforceinturningprocessbyusingartificialneuralnetwork
_version_	1718397159174307840

Prediction of Cutting Force in Turning Process by Using Artificial Neural Network

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