Fraunhofer-Institut für Produktionsanlagen und Konstruktionstechnik IPK

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  • Publication
    Transferability of ANN-generated parameter sets from welding tracks to 3D-geometries in Directed Energy Deposition
    ( 2022-11-04)
    Marko, Angelina
    ;
    Bähring, Stefan
    ;
    Raute, Maximilian Julius
    ;
    Biegler, Max
    ;
    Rethmeier, Michael
    Directed energy deposition (DED) has been in industrial use as a coating process for many years. Modern applications include the repair of existing components and additive manufacturing. The main advantages of DED are high deposition rates and low energy input. However, the process is influenced by a variety of parameters affecting the component quality. Artificial neural networks (ANNs) offer the possibility of mapping complex processes such as DED. They can serve as a tool for predicting optimal process parameters and quality characteristics. Previous research only refers to weld beads: a transferability to additively manufactured three-dimensional components has not been investigated. In the context of this work, an ANN is generated based on 86 weld beads. Quality categories (poor, medium, and good) are chosen as target variables to combine several quality features. The applicability of this categorization compared to conventional characteristics is discussed in detail. The ANN predicts the quality category of weld beads with an average accuracy of 81.5%. Two randomly generated parameter sets predicted as “good” by the network are then used to build tracks, coatings, walls, and cubes. It is shown that ANN trained with weld beads are suitable for complex parameter predictions in a limited way.
  • Publication
    Gear Wheel Finishing with Abrasive Brushing Tools to Improve the Surface Quality of Tooth Flanks for the Industrial Application
    ( 2022)
    Gülzow, Bernhard
    ;
    Uhlmann, Eckart
    A high surface quality of tooth flanks can improve the service life and the performance of gears, as well as reduce acoustic emissions. However, high demands on the gear geometry pose a challenge for the finishing of tooth flank surfaces because the dimensional accuracy that can be achieved with modern grinding processes must not be impaired by the finishing process. A preceding study has shown fundamentally that profiled abrasive brushing tools can be used to improve the quality of individual tooth flank surfaces. Due to the integration into the grinding machine, it represents a promising alternative to common finishing applications. Before the process can be used in an industrial environment, process reliability and tool life must be examined. For this purpose, complete reference gearwheels (39 × 10) were finished with the brushing tools. It could be shown that the surface roughness can be reliably reduced by ΔRa ≈ 0.2 µm by using a single brush for an entire gearwheel without changing the gear geometry. In addition to the influence of the tool specifications on the work result, the influence of the initial roughness after grinding was considered in particular. It was found that the achievable surface roughness depends significantly on the depth of the grinding grooves, as these are retained as desired, while the roughness peaks are fully smoothed. Furthermore, a device for the machine-integrated profiling and dressing of brushing tools was successfully designed, implemented, and tested.