No abstract

No abstract

The formation of thermally and mechanically induced near-surface microstructures in the form of white layers leads to different hardness properties in these areas. Therefore, this paper conducts systematic surface hardness measurements and uncertainty quantification utilizing the Monte Carlo Method (MCM) in accordance with the Guide to the Expression of Uncertainty in Measurement (GUM). Furthermore, several meta-models describing the hardness course in relationship to the material depth are used to model this nonlinear relationship via machine learning. The evaluation and selection of the optimal model considers the trade-off between measurement uncertainty and prediction quality in terms of mean squared error (MSE). The resulting measurement uncertainty is to be used for the calibration of a non-destructive micromagnetic material sensor. This will then be implemented for in-process monitoring in the outer diameter longitudinal turning process. This should make it possible to detect white layers during machining and to avoid them accordingly by controlling the machine parameters. By means of a soft sensor, the corresponding target value is to be derived from the micromagnetic material sensor measurement.

The rapidly advancing trend towards miniaturization in the series production of gears confronts quality assurance with new challenges. In this context, metrological technologies as well as expertise from the field of macro gears can only be transferred to a limited extent. Inline integration of metrology into micro gear production has not yet been implemented in a practicable way. This publication extends the current limits of micro gear quality assurance to date by qualifying the optical method of focus variation technology for complete inline measurements of micro gears in series production time. In detail, this work includes the development of a measurement program by means of Design of Experiments, the establishment of a practicable cleaning process, the evaluation of resulting measurement uncertainties, and a process capability analysis. Consequently, the focus variation technology is qualified for fast, three-dimensional measurements of micro gears with respectively low measurement uncertainties.

The aim of this research project is the extension of the shaping boundaries for the radial axial rolling of rings with an outer profile. Basis for this extension is the displacement of the ring from the longitudinal machine axis during the rolling process. This displacement causes a change of the deformation ratios for the benefit of the main roll, resulting in an improved material flow behaviour and thereby improving the profile filling of the ring. To enable the usage of this displacement approach the ring rolling machine located at the Chair of Production Systems had to be equipped with a displacement controller. To use the displacement without damaging the ring, the additional forces inflicted by the displacement have to be limited. Therefore a force controller is developed that calculates and sets the forces of the centering arms according to the current geometric and mechanical properties of the ring. Concluding to the theoretical development of the displacement and force controllers experimental rollings are presented that prove the capabilities of the controllers, the positive effects of the displacing and guidelines on how to set strategies for the displacement.