2013
DOI: 10.1155/2013/932094
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Prediction of Surface Roughness When End MillingTi6Al4VAlloy Using Adaptive Neurofuzzy Inference System

Abstract: 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 complex problems like metal cutting processes. The present study used adaptive neurofuzzy inference system for the purpose of predicting the surface roughness when end milling Ti6Al4V alloy with coated (PVD) and unco… Show more

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Cited by 3 publications
(2 citation statements)
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“…ANFIS has recently been proven to be another effective prediction tool in engineering applications by several researchers. Al-Zubaidi et al [ 15 ] investigated the ANFIS model's predictability in anticipating surface roughness in milling Ti–6Al–4V alloy and found a minimal root mean square error (RMSE) of 0.1030. The predictability of the ANFIS model changes with membership functions.…”
Section: Introductionmentioning
confidence: 99%
“…ANFIS has recently been proven to be another effective prediction tool in engineering applications by several researchers. Al-Zubaidi et al [ 15 ] investigated the ANFIS model's predictability in anticipating surface roughness in milling Ti–6Al–4V alloy and found a minimal root mean square error (RMSE) of 0.1030. The predictability of the ANFIS model changes with membership functions.…”
Section: Introductionmentioning
confidence: 99%
“…Milling is removing allowance from the billet by means of the various milling cutters. The roughness formation of the machined surface of the part when milling on the machine with the computer numerical control (CNC) is presented in the number of the scientific works [2][3][4][5][6][7][8][9]. Since milling takes place in the conditions of removing variable allowance and constantly cutting the teeth into the billet material, it is necessary to increase rigidity of the cutting tool and the billet for reducing the surface roughness.…”
Section: Introductionmentioning
confidence: 99%