Now showing 1 - 10 of 2550
No Thumbnail Available
Publication

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.

No Thumbnail Available
Publication

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.

No Thumbnail Available
Publication

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.

No Thumbnail Available
Publication

In situ microstructure analysis of Inconel 625 during laser powder bed fusion

2022 , Schmeiser, F. , Krohmer, E. , Wagner, C. , Schell, N. , Uhlmann, E. , Reimers, W.

Laser powder bed fusion is an additive manufacturing process that employs highly focused laser radiation for selective melting of a metal powder bed. This process entails a complex heat flow and thermal management that results in characteristic, often highly textured microstructures, which lead to mechanical anisotropy. In this study, high-energy X-ray diffraction experiments were carried out to illuminate the formation and evolution of microstructural features during LPBF. The nickel-base alloy Inconel 625 was used for in situ experiments using a custom LPBF system designed for these investigations. The diffraction patterns yielded results regarding texture, lattice defects, recrystallization, and chemical segregation. A combination of high laser power and scanning speed results in a strong preferred crystallographic orientation, while low laser power and scanning speed showed no clear texture. The observation of a constant gauge volume revealed solid-state texture changes without remelting. They were related to in situ recrystallization processes caused by the repeated laser scanning. After recrystallization, the formation and growth of segregations were deduced from an increasing diffraction peak asymmetry and confirmed by ex situ scanning transmission electron microscopy.

No Thumbnail Available
Publication

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.

No Thumbnail Available
Publication

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.

No Thumbnail Available
Publication

Schweißtechnik: KI-basierte Parametrierung

2022-05-16 , Baumann, Anja , El-Sari, Bassel , Fromme, Dirk

Für die Parametrierung von Schweißverbindungen werden viele Schweißversuche und ein fundiertes Fachwissen benötigt. Die richtigen Parameter auf Anhieb zu finden gleicht der Suche nach der Nadel im Heuhaufen. Mithilfe von künstlicher Intelligenz kann solch eine Suche stark vereinfacht werden. Die Algorithmen, einmal richtig trainiert, können effizient die nahezu richtigen Parameter liefern und somit die Vorserienkosten reduzieren.

No Thumbnail Available
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.

No Thumbnail Available
Publication

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.

No Thumbnail Available
Publication

Acoustic emission-based process monitoring in the milling of carbon fibre-reinforced plastics

2022 , Uhlmann, E. , Holznagel, Tobias

Milling of fibre-reinforced plastics is a challenging task. The highly abrasive fibres lead to high tool wear and coating failures, which cause increasing process forces and temperatures. Machining with a worn tool, in turn, can result in unwanted workpiece damages such as delamination or fibre protrusion. Reliable monitoring of the process must therefore be able to detect damages to the milling tool and the workpiece alike. The presented process monitoring approach measures the acoustic emission generated by the milling tool cutting edge entering the workpiece with a sensor attached to the tool holder. Specific acoustic emission frequency spectra and waveforms are emitted in the cutting zone for different tool wear states. Coating failures as well as other acoustic emission events due to workpiece damages can be robustly detected and distinguished by feature extraction and signal processing as well. The developed setup, the monitoring parameterisation techniques and signal processing algorithms as well as experimental and monitoring results are presented and discussed in this paper.