Surface morphology prediction model for milling operations

The capability of estimating the surface quality of workpieces in machining is still a challenging goal. The morphology of the processed surfaces does not only depend on nominal tool geometry and on machining parameters but it is also affected by several complex cutting phenomena and deviations from nominal conditions. In this paper, a framework model for estimating the surface texture in milling operations was developed. The model allows considering various tool geometries and the corresponding alignment/mounting errors. Since the back cutting phenomenon is adequately formalized, the model is particularly suitable for estimating the surface topography in face milling. Although the model does not consider the contribution due to the cutting forces, it is suitable for being fed by measured tool vibrations. The predicting capabilities of the conceived model were tested considering a high-feed milling operation that typically generates complex patterns on the processed surfaces. The model validation was carried out comparing the numerical and the real machined surface morphology. The analysis confirmed that the surface morphology can be predicted with negligible errors.