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30. 4. 2018.
Comparative Analysis of Surface Quality Prediction Models
The paper presents a comparative analysis of the models for predicting machined surface quality developed by the application of multiple regression and artificial neural networks. The models were developed using experimental data for the mean arithmetic deviation of surface roughness and the axial cutting force obtained by implementing the Taguchi experiment plan. Comparative analysis of the models has shown that artificial neural networks give the best results in terms of predicting the mean arithmetic deviation of surface roughness on the basis of process parameters and axial cutting force.