Statistical Process Modelling for Machining of Inhomogeneous Mineral Subsoil

Abstract

Because in the machining process of concrete tool wear and production time are very cost sensitive factors the adaption of the tools to the particular machining processes is of major interest. We show how statistical methods can be used to model the influences of the process parameters to the forces affecting the workpiece as well as the chip removal rate and the wear rate of the used diamond. Based on these models a geometrical simulation model can be derived which will help to predetermine optimal parameter settings for specific situations. As the machined materials are in general abrasive, usual discretized simulation methods like Finite Elements Models can not be applied. Hence our approach is another type of discretization namely subdividing both material and diamond grain into their Delaunay tessellations and interpreting the resulting micropart connections as predetermined breaking points. Then the process is iteratively simulated and in each iteration the interesting entities are computed.

Model based optimization of a statistical simulation model for single diamond grinding

“…In this section we discuss the time complexity of the presented scratch track model, the Raabe et al ( [13], [14], [15]) model and the Herbrandt et al [5] model, which includes first simplifications of the Raabe et al [13] model in order to reduce the time complexity.…”

“…In the model of Raabe et al ( [13], [14], [15]) the workpiece is simulated with two sets of n R and k R points, where n R < k R (coarse and fine lattice). For each point of the first set a value from a Gaussian random field (time complexity O n 3 R , [9]) is sampled.…”

“…Inspired by the work of Raabe et al ([13], [14], [15]) we derive a force model based on the removed material volume and the material heterogeneity (see sec. 3).…”