A novel analytical model for predicting ploughing effect on machined wall surface topography considering tool wear during slot milling process

The published prediction models of machined surface topography assume that the whole materials in the volume to be cut could be entirely removed by cutting tool-edge in machining processes. The effects of the ploughing effect due to tool wear on the machined surface are ignored. This study proposes a new method for predicting the machined wall surface topographies and roughness in slot milling operations. The ploughing effects of worn tool- edge on the machined slot wall surface topographies are investigated in this research for the first time. The wall surface profile is divided into two components in workpiece coordinate system. The first component is the kinematic surface profile, which is modeled and solved by the kinematic principle and Z-MAP algorithm. The second component is the wear-induced surface profile, which is caused by the ploughing effect due to the worn tool-edge. The wear-induced surface profile is revealed through ploughing effects, which can be calculated based on elastic recovery theory and volume invariance principle. The wear-induced surface profile is transformed into workpiece coordinate system by using the proposed algorithm, firstly. The 2D surface profiles of milled slot walls are then obtained by superimposing the kinematic profiles with the wear-induced surface profiles in workpiece coordinate system. Finally, the 3D topographies of the milled slot walls can be reconstructed by integrating the 2D surface profiles. The respective influence mechanisms of worn tool-edges on slot wall topographies due to up- milling and down-milling are investigated separately. This proposed method can be integrated into CAM programs in the form of modules to accurately predict the machined surface topographies and surface roughness in slot milling.