Prediction of Surface Roughness When End Milling Ti6Al4V Alloy Using Adaptive Neurofuzzy Inference System

Surface roughness is considered as the quality index of the machine parts. Many diverse techniques have been applied in modelling metal cutting processes. Previous studies have revealed that artificial intelligence techniques are novel soft computing methods which fit the solution of nonlinear and c...

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Bibliographic Details
Main Authors: Salah Al-Zubaidi, Jaharah A. Ghani, Che Hassan Che Haron
Format: Article
Language:English
Published: Wiley 2013-01-01
Series:Modelling and Simulation in Engineering
Online Access:http://dx.doi.org/10.1155/2013/932094
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