Simulation uncertainty determination of single flank rolling tests using monte carlo simulation and skin model shapes for zero defect manufacturing of micro gears

Abstract

Simulative gear rolling enables the integration of function-oriented quality assurance into production processes for Zero Defect Manufacturing (ZDM). A simulated single flank rolling test can be carried out using inline measurements. With the aim of integration for the control of production parameters and a functional forecast, this paper aims at an uncertainty evaluation of an analytic tooth contact analysis software. Based on optical measurements of focus variation technology and actual micro gear test facility procedures, task-specific simulation uncertainties for the four parameters of the single flank rolling inspection are evaluated. This approach uses an optimized Latin Hypercube Sampling (LHS) approach to generate artificial gear point clouds with specified deviations for a Monte Carlo simulation (MCS) based on an adaptive scheme of the Guide to the Expression of Uncertainty in Measurement (GUM) for determining model uncertainties. It was shown that the fast simulative results have a relatively low expanded uncertainty of less than 6 µm. The use case is a high-volume micro-production.