Modeling of the Grinding Wheel Topography Depending on the Recipe-Dependent Volumetric Composition

Abstract

The prediction of the grinding process result, such as the workpiece surface quality or the state of the edge zone depending on the used grinding wheel is a great challenge for todays manufacturers and users of grinding tools. This is mainly caused by inadequate predictability of the forces and temperatures acting in the process, which depend on the topography of the grinding wheel coming into contact with the workpiece during the grinding process. The topography of a grinding wheel depends, beside the dressing process, on the structure of the grinding wheel, which is determined by its recipe-dependent volumetric composition. The structure of a grinding tool therefore determines its application behavior strongly. As a result, the knowledge-based prediction of the grinding wheel topography and its influence on the machining behavior is only possible if the recipe-dependent grinding wheel structure is known. In this paper, an innovative approach for modeling the grinding wheel structure and the resultant grinding wheel topography is discussed. The overall objective of the underlying research project was to create a mathematical-generic grinding wheel model in which the spatial arrangement of the components grains, bond and pores is simulated in a realistic manner starting from the recipe-dependent volumetric composition of a grinding wheel. With this model it is possible to determine the resulting grinding wheel structure and the grinding wheel topography of vitrified and synthetic resin-bonded CBN grinding wheels and thus to predict their application behavior. The originality of the present research results is a generic approach for the modeling of grinding wheels, taking into account the entire grinding wheel structure and build up the topography based on it. Using original mathematical methods, the components of grinding wheels were analyzed and distribution functions of the components were determined. Thus the statistical character of the grinding wheel structure was taken into account. In future, the presented model opens new perspectives in order to optimize and to increase the productivity of grinding processes.