DOIONLINE 
DOIONLINE Publish In |
International Journal of Mechanical and Production Engineering (IJMPE)-IJMPE |
 Journal Home Volume Issue |
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Issue |
Volume-5,Issue-7 ( Jul, 2017 ) | |||||||||
Paper Title |
Optimization and Predictive Modelling on Cutting Force of Duplex Stainless Steel using Artificial Neural Network | |||||||||
Author Name |
Ahmet Mavi, Semih Ozden, Gultekin Uzun | |||||||||
Affilition |
OSTIM Vocational College, Department of Mechatronics, Gazi University, Turkey Department of Manufacturing Engineering, Faculty of Technology, Gazi University, Turkey | |||||||||
Pages |
81-85 | |||||||||
Abstract |
In this study, a prediction model was developed for cutting force of Duplex Stainless Steel (1.4462) by using Artificial Neural Network (ANN). Machinability tests were carried out under dry conditions at the CNC lathe with the cutting parameters selected in accordance with ISO 3685. In the experiment, cutting force depending on cutting parameters (cutting speed, chip angle and feed rate) were measured. These parameters were used for ANN as input parameters (training and testing). Output parameters of ANN were cutting force and temperature values. The accuracy of ANN performance evaluated by regression analysis with comparing experimental and predicted. ANN model provided highly accurate and consistent prediction for all output parameters. Keywords - Duplex Stainless Steel, Neural Network, Cutting Force | |||||||||
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