Predictive modeling of surface finish in fine grinding

Grinding is on of the important machine processes when tight tolerances and fine surface finishes are required. However, due to the large number of process parameters involved, predicting the outcome of a grinding process is not a trivial task. This thesis describes the development of a predictive model of surface finish in the fine surface grinding process.

The surface topography of a grinding wheel was analyzed using a laser scanner. The statistical distribution for grain protrusion heights and the transvere and longitudinal spacing of grains were determined. Each protruded grain is counted as a cutting edge that engages with the workpiece to generate a unique chip. A solid modeller was used to model an individiaul chip as an ellipsoid. The measured topography of the grinding wheel, together with a kinematic relationship in surface grinding, was used to determine the goemetrical characteristics of the ellipsoid. The solid modeller was then used to model the chip removal process by successive grains.

The surface roughtness predicted by the model was compared with experiemental results. The results showed good consistency between the model and the actual surface properties.