MODELLING OF SURFACE ROUGHNESS PERFORMANCE OF COATED CEMENTED CARBIDE GROOVE CUTTING TOOL VIA ARTIFICIAL NEURAL NETWORKS

Authors : Ahmet PİNAR

Pages : 901-910

View : 16 | Download : 10

Publication Date : 2011-03-26

Article Type : Other Papers

Abstract :Normal 0 21 false false false TR X-NONE X-NONE MicrosoftInternetExplorer4 The objective of the presented study is to model the effects of cutting speed, feed rate and depth of cut on the surface roughness insert ignore into journalissuearticles values(roughness average, Ra); in the turning process carried out by the grooving cutting tool by using Artificial Neural Network insert ignore into journalissuearticles values(ANN);. To realize this aim, twenty seven specimens are machined at the cutting speeds of 100, 140 and 180m/min, feed rates of 0.05, 0.15 and 0.25mm/rev, and cutting depth of 0.6, 1.3 and 2 mm in wet conditions. Data from these experiments are used in the training of ANN. When we compare the experimental results with the ANN ones, it is observed that proposed method is applied with an error rate of 8.14% successfully. Key Words : S urface roughness, ANN, turning, modelling, groove cutting tool.    
Keywords : Surface roughness, ANN, turning, modelling, groove cutting tool