Fraunhofer-Institut für Produktionsanlagen und Konstruktionstechnik IPK

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Adaptive Reparatur-Prozesskette

2023-02-11 , Müller, Vinzenz , Mönchinger, Stephan , Colombo, Giovanna Fiocco , Biegler, Max , Rethmeier, Michael

Das additive Fertigungsverfahren Laser-Powder Directed Energy Depositon (LP-DED), kombiniert mit automatisierten Reverse-Engineering-Ansätzen, bietet die Möglichkeit, Bauteile effizient zu reparieren. Durch intelligente Algorithmen können im sogenannten Scangineering 3D-Scandaten von Bauteilen vorverarbeitet, ausgerichtet und parametrisiert werden. Die erkannten geometrischen Defekte werden zur Errechnung der Werkzeugwege für den additiven Aufbau verwendet und mittels des LP-DED-Prozesses aufgeschweißt und repariert. Dabei kommen vor allem die Vorteile der flexiblen Prozessführung, ein hoher Automatisierungsgrad und gute Reproduzierbarkeit zum Tragen.

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Retaining Mechanical Properties of GMA-Welded Joints of 9%Ni Steel Using Experimentally Produced Matching Ferritic Filler Metal

2022-11-30 , El-batahgy, Abdel-monem , Elkousy, Mohamed Raafat , Al-Rahman, Ahmed Abd , Gumenyuk, Andrey , Rethmeier, Michael , Gook, Sergej

Motivated by the loss of tensile strength in 9%Ni steel arc-welded joints performed using commercially available Ni-based austenitic filler metals, the viability of retaining tensile strength using an experimentally produced matching ferritic filler metal was confirmed. Compared to the austenitic Ni-based filler metal (685 MPa), higher tensile strength in gas metal arc (GMA) welded joints was achieved using a ferritic filler metal (749 MPa) due to its microstructure being similar to the base metal (645 MPa). The microstructure of hard martensite resulted in an impact energy of 71 J (−196 °C), which was two times higher than the specified minimum value of ≥34 J. The tensile and impact strength of the welded joint is affected not only by its microstructure, but also by the degree of its mechanical mismatch depending on the type of filler metal. Welds with a harder microstructure and less mechanical mismatch are important for achieving an adequate combination of tensile strength and notched impact strength. This is achievable with the cost-effective ferritic filler metal. A more desirable combination of mechanical properties is guaranteed by applying low preheating temperature (200 °C), which is a more practicable and economical solution compared to the high post-weld heat treatment (PWHT) temperature (580 °C) suggested by other research.

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Laserstrahlhybridschweißen von Türmen für Windkraftanlagen

2022-08-29 , Üstündag, Ömer , Bakir, Nasim , Brunner-Schwer, Christian , Knöfel, Frieder , Gook, Sergej , Rethmeier, Michael , Gumenyuk, Andrey

Das Laserstrahlhybridschweißen ist beim Schweißen von Türmen für Windkraftanlagen eine Alternative zum Unterpulverschweißen von Dickblechen in Mehrlagentechnik und bietet hier ökonomische und ökologische Vorteile. Der industrielle Einsatz des Verfahrens ist jedoch durch prozessspezifische Herausforderungen eingeschränkt. Die im Beitrag beschriebene kontaktlose elektromagnetische Badstütze dient zur Erweiterung des Verfahrenspotenzials im Dickblechbereich >15 mm.

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More sustainable in the automobile with tailor welded blank (TWB)

2022-07-01 , Lemke, Josefine , Weber, Joshua , Kompenhans, Moritz , Höfemann, Matthias , Joos, Paul

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Implementing digital twins in existing infrastructures

2023 , Lünnemann, Pascal , Lindow, Kai , Goßlau, Leo

Digital twins can offer various added values for companies. As part of a three-year research project, we are investigating the methodological approach, for building digital twins in existing infrastructures. In particular, the functional requirements of future users will be addressed, as this is less focused in existing approaches. Within the framework of this publication, we discuss the applied methodology as well as the created models and concepts. Initial insights were gained in the simultaneous development of digital twins in parallel projects with use cases for electric motors, production process monitoring and maintenance of gas turbine components. In detail, it becomes clear that software development methods (e.g. use cases, user stories, scenario development) are a good way to describe the expected added value functions. It is essential to involve the future users in the development as early as possible. Transferring the necessary functions identified in this way into a functional architecture shows that this architecture is mostly independent of the use case. Likewise, the IT systems used here hardly vary at all. Overall, it shows that a methodical approach can be followed in the development and the implementation can have a high degree of similarity, even in very different use cases, while the exact design, depending on these use cases, is very diverse.

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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.

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Joining 30 mm Thick Shipbuilding Steel Plates EH36 Using a Process Combination of Hybrid Laser Arc Welding and Submerged Arc Welding

2022-08-04 , Gook, Sergej , Midik, Ahmet , Biegler, Max , Gumenyuk, Andrey , Rethmeier, Michael

This article presents a cost-effective and reliable method for welding 30 mm thick sheets of shipbuilding steel EH36. The method proposes to perform butt welding in a two-run technique using hybrid laser arc welding (HLAW) and submerged arc welding (SAW). The HLAW is performed as a partial penetration weld with a penetration depth of approximately 25 mm. The SAW is carried out as a second run on the opposite side. With a SAW penetration depth of 8 mm, the weld cross-section is closed with the reliable intersection of both passes. The advantages of the proposed welding method are: no need for forming of the HLAW root; the SAW pass can effectively eliminate pores in the HLAW root; the high stability of the welding process regarding the preparation quality of the weld edges. Plasma cut edges can be welded without lack of fusion defects. The weld quality achieved is confirmed by destructive tests.

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Mittels Scangineering und Schweiß-Knowhow zum reparierten Umformwerkzeug

2022-12-19 , Biegler, Max , Mönchinger, Stephan , Müller, Vinzenz , Rethmeier, Michael

Zum wirtschaftlichen und nachhaltigen Einsatz von Stanz- und Formwerkzeugen ist in der Regel eine Reparatur der verschlissenen Werkzeuge erforderlich. Das Additive Fertigungsverfahren Laser-Powder Directed Energy Depositon (LP-DED) in Kombinationen mit intelligenten Reverse-Engineering-Ansätzen bietet die Möglichkeit, Bauteile materialschonend und effizient zu reparieren.

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Prognose von Qualitätsmerkmalen durch Anwendung von KI-Methoden beim "Directed Energy Deposition"

2022-10 , Marko, Angelina , Bähring, Stefan , Raute, Maximilian Julius , Biegler, Max , Rethmeier, Michael

Dieser Beitrag enthält die Ergebnisse eines im Rahmen der DVS Forschung entwickelten Ansatzes zur Qualitätssicherung im Directed Energy Deposition. Es basiert auf der Verarbeitung verschiedener während des Prozesses gesammelter Sensordaten unter Anwendung Künstlicher Neuronale Netze (KNN). So ließen sich die Qualitätsmerkmale Härte und Dichte auf der Datenbasis von 50 additiv gefertigten Probenwürfel mit einer Abweichung < 2 % vorhersagen. Des Weiteren wurde die Übertragbarkeit des KNN auf eine Schaufelgeometrie untersucht. Auch hier ließen sich Härte und Dichte hervorragend prognostizieren (Abweichung < 1,5 %), sodass der Ansatz als validiert betrachtet werden kann.

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Nachhaltiger im Automobil mit TWB

2022-07-30 , Lemke, Josefine , Weber, Joshua , Kompenhans, Moritz Niklas , Höfemann, Matthias , Joos, Paul

CO2-Footprint von Fahrzeugen wird maßgeblich durch ihr Gewicht bestimmt. Spezielle Blechplatinen - bislang noch nicht in Serie eingesetzte Tailor Welded Blanks aus höchstfesten Stählen mit Festigkeiten von 1000 MPa - können diesen verringern. Die Verarbeitung geschweißter höchstfester Platinen kann jedoch noch zu Diskontinuität im Bauteil führen. Den Prozess rein experimentell auszulegen ist teuer und verschwendet Material und Ressourcen. Dem begegnet das BMWK-Projekt TWBlock mit numerischen Simulationen und deren Absicherung durch die Blockchain-Technologie über die gesamte Prozess- und Wertschöpfungskette.

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