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

  • Marwa Qasim Ibraheem Department of Production Engineering and Metallurgy/ University of Technology/ Baghdad/ Iraq

Abstract

       

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.

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Published
2020-06-01
How to Cite
Ibraheem, M. (2020). Prediction of Cutting Force in Turning Process by Using Artificial Neural Network. Al-Khwarizmi Engineering Journal, 16(2), 34- 46. https://doi.org/10.22153/kej.2020.04.002