Paper Title :Optimization and Predictive Modelling on Cutting Force of Duplex Stainless Steel using Artificial Neural Network

Author :Ahmet Mavi, Semih Ozden, Gultekin Uzun

Article Citation :Ahmet Mavi ,Semih Ozden ,Gultekin Uzun , (2017 ) " Optimization and Predictive Modelling on Cutting Force of Duplex Stainless Steel using Artificial Neural Network " , International Journal of Mechanical and Production Engineering (IJMPE) , pp. 81-85, Volume-5,Issue-7

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

Type : Research paper

Published : Volume-5,Issue-7

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