Study on the prediction model of surface roughness for side milling operations

The paper presents a feasibility study on prediction of surface roughness in side milling operations using the different polynomial networks. A series of experiments using S45C steel plates is conducted to study the effects of the various cutting parameters on surface roughness. The different polynomial networks for predicting surface roughness are developed using the abductive modeling technique and based on the F-ratio to select their input variables. The results show that the developed models achieve high predicting capability on surface roughness, especially for the case of smaller flank wear of peripheral cutting edge. Hence, it can be concluded that the developed polynomial-network models posses promising potential in the application of predicting surface roughness in side milling operations.

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