MODELLING OF SURFACE ROUGHNESS PERFORMANCE OF COATED CEMENTED CARBIDE GROOVE CUTTING TOOL VIA ARTIFICIAL NEURAL NETWORKS
DOI:
关键词: Cutting tool 、 Cemented carbide 、 Depth of cut 、 Artificial neural network 、 Structural engineering 、 Surface roughness 、 Groove (music) 、 Engineering 、 Surface finish
摘要: Normal 0 21 false TR X-NONE MicrosoftInternetExplorer4 The objective of the presented study is to model effects cutting speed, feed rate and depth cut on surface roughness (roughness average, Ra) in turning process carried out by grooving tool using Artificial Neural Network (ANN). To realize this aim, twenty seven specimens are machined at speeds 100, 140 180m/min, rates 0.05, 0.15 0.25mm/rev, 0.6, 1.3 2 mm wet conditions. Data from these experiments used training ANN. When we compare experimental results with ANN ones, it observed that proposed method applied an error 8.14% successfully. Key Words : S urface roughness, ANN, turning, modelling, groove tool.
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