Modeling the surface roughness and cutting force for turning

In this paper, an abductive network is adopted to construct a prediction model for surface roughness and cutting force. This network is composed of a number of functional nodes, which are self-configured to form an optimal network hierarchy by using a predicted square error (PSE) criterion. Once the process parameters (cutting speed, feed rate and depth of cut) are given, the surface roughness and cutting force can be predicted by this network. To verify the accuracy of the abductive network, regression analysis has been adopted in the paper to develop a second prediction model for surface roughness and cutting force. Comparison of the two models indicates that the prediction model developed by the abductive network is more accurate than that by regression analysis. Experimental results are provided to confirm the effectiveness of this approach.