Fraunhofer-Institut für Produktionsanlagen und Konstruktionstechnik IPK

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  • Publication
    Analyse und Nutzung von Aluminium-Bronze-Schleifstaub für das Laser-Pulver-Auftragsschweißen
    ( 2022-12)
    Müller, Vinzenz
    ;
    Marko, Angelina
    ;
    Kruse, Tobias
    ;
    Biegler, Max
    ;
    Rethmeier, Michael
    Die additive Fertigung verspricht ein großes Potenzial für den maritimen Sektor. Insbesondere Directed Energy Deposition (DED) Verfahren bieten die Möglichkeit, großvolumige maritime Bauteile wie Propellernaben oder -schaufeln herzustellen. Bei der Nachbearbeitung solcher Bauteile fällt in der Regel eine große Menge an Schleifabfällen an. Ziel des vorgestellten Projekts ist die Entwicklung einer nachhaltigen zirkulären AM-Prozesskette für maritime Komponenten auf Basis von Aluminiumbronze-Schleifresten. Dazu soll das Material wiederaufbereitet und anschließend als Rohmaterial für die Herstellung von Schiffspropellern im Laser-Pulver DED-Verfahren verwendet werden. In der vorliegenden Arbeit werden Schleifabfälle mittels dynamischer Bildanalyse untersucht und mit kommerziellem DED-Pulver verglichen. Anschließend werden Probengeometrien aus Schleifstaub gefertigt und durch metallographische Schliffe und REM/EDX analysiert.
  • 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
    A study of the magnetohydrodynamic effect on keyhole dynamics and defect mitigation in laser beam welding
    ( 2022)
    Meng, X.
    ;
    Bachmann, M.
    ;
    Artinov, A.
    ;
    Rethmeier, Michael
    In this paper, the highly transient keyhole dynamics, e.g., laser absorption, keyhole geometry, and fluctuation, etc., under a magnetic field are investigated using an experimental approach and multi-physical modeling. The model provides accurate predictions to the variation of penetration depth and weld pool profiles caused by the MHD effect, which is validated by the measurements of optical micrographs and in-situ metal/glass observation. The micro-X-ray computed tomography shows a remarkable reduction of keyhole-induced porosity with the magnetic field. The correlation between the porosity mitigation and the weld pool dynamics influenced by the magnetic field is built comprehensively. It is found that the magnetic field gives a direct impact on the laser energy absorption at the keyhole front wall by changing the protrusion movement. The porosity mitigation comes from multiple physical aspects, including keyhole stabilization, widening of the bubble floating channel, and the electromagnetic expulsive force. Their contributions vary according to the bubble size. The findings provide a deeper insight into the relationship between electromagnetic parameters, keyhole dynamics, and suppression of keyhole-relevant defects.