Now showing 1 - 10 of 2547
  • Publication
    Transferability of ANN-generated parameter sets from welding tracks to 3D-geometries in Directed Energy Deposition
    ( 2022-11-04)
    Marko, Angelina
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    Bähring, Stefan
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    Raute, Maximilian Julius
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    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
    Prognose von Qualitätsmerkmalen durch Anwendung von KI-Methoden beim "Directed Energy Deposition"
    ( 2022-10)
    Marko, Angelina
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    Bähring, Stefan
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    Raute, Maximilian Julius
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    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.
  • Publication
    Laserstrahlhybridschweißen von Türmen für Windkraftanlagen
    ( 2022-08-29)
    Üstündag, Ömer
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    Bakir, Nasim
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    Knöfel, Frieder
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    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.
  • Publication
    Nachhaltiger im Automobil mit TWB
    ( 2022-07-30) ;
    Weber, Joshua
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    Kompenhans, Moritz Niklas
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    Höfemann, Matthias
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    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.
  • Publication
    Schweißtechnik: KI-basierte Parametrierung
    ( 2022-05-16)
    Baumann, Anja
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    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.
  • Publication
    Agiles Prozessmanagement mittels Ambidextrie
    ( 2022) ;
    Lange, Annika
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    Busse, Dirk
    Aufgrund der vielfältigen und überlappenden Einflüsse aus dem Unternehmensumfeld (z. B. Pandemie, Chip-Krise, Naturkatastrophen) müssen Entscheidungen sowohl auf Basis von unternehmensinternen Daten (z. B. Liquidität) als auch Umfeldinformationen (z. B. Technologie-trends) getroffen werden. Anschließend sind Maßnahmen abzuleiten und - neben den regulären Unternehmensprozessen - umzusetzen. In diesem Beitrag wird ein Ansatz für die Informationsvernetzung und -bereitstellung für agiles Prozessmanagement vorgestellt.
  • Publication
    Hybrid laser-arc welding of laser- and plasma-cut 20-mm-thick structural steels
    ( 2022)
    Üstündag, Ömer
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    Bakir, Nasim
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    It is already known that the laser beam welding (LBW) or hybrid laser-arc welding (HLAW) processes are sensitive to manufacturing tolerances such as gaps and misalignment of the edges, especially at welding of thick-walled steels due to its narrow beam diameter. Therefore, the joining parts preferably have to be milled. The study deals with the influence of the edge quality, the gap and the misalignment of edges on the weld seam quality of hybrid laser-arc welded 20-mm-thick structural steel plates which were prepared by laser and plasma cutting. Single-pass welds were conducted in butt joint configuration. An AC magnet was used as a contactless backing. It was positioned under the workpiece during the welding process to prevent sagging. The profile of the edges and the gap between the workpieces were measured before welding by a profile scanner or a digital camera, respectively. With a laser beam power of just 13.7 kW, the single-pass welds could be performed. A gap bridgeability up to 1 mm at laser-cut and 2 mm at plasma-cut samples could be reached respectively. Furthermore, a misalignment of the edges up to 2 mm could be welded in a single pass. The new findings may eliminate the need for cost and time-consuming preparation of the edges.
  • Publication
    Methodology for a reverse engineering process chain with focus on customized segmentation and iterative closest point algorithms
    ( 2022) ;
    Schröder, Robert
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    Stark, Rainer
    One-off construction is characterized by a multiplicity of manual manufacturing processes whereby it is based on consistent use of digital models. Since the actual state of construction does not match the digital models without manually updating them, the authors propose a method to automatically detect deviations and reposition the model data according to reality. The first essential method is based on the ""Segmentation of Unorganized Points and Recognition of Simple Algebraic Surfaces"" presented by Vanco et al.. The second method is the customization of the iterative closest point (ICP) algorithm. The authors present the overall structure of the implemented software, based on open source and relate it to the general reverse engineering (RE) framework by Buonamici et al.. A highlight will be given on: the general architecture of the software prototype; a customized segmentation and clustering of unorganized points and recognition of simple algebraic surfaces; the deviation analysis with a customized iterative closest point (CICP) algorithm Especially in the field of one-off construction, characterized by small and medium companies, automated assessment of 3D scan data during the design process is still in its infancy. By using an open source environment progress for consistent use of digital models could be accelerated.
  • Publication
    In situ microstructure analysis of Inconel 625 during laser powder bed fusion
    ( 2022)
    Schmeiser, F.
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    Krohmer, E.
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    Wagner, C.
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    Schell, N.
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    Uhlmann, E.
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    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.
  • Publication
    Micro-texture dependent temperature distribution of CVD diamond thick film cutting tools during turning of Ti-6Al-4V
    ( 2022) ;
    Schröter, D.
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    Machining titanium alloys such as Ti-6Al-4V results in a high thermomechanical load on cutting tools and consequently short tool lifes. With respect to a necessary reduction of the resulting cutting tool temperatures, ultrashort pulse (USP) laser fabricated micro-textured rake faces offer direct supply of cooling lubricant into the cutting zone and lead to a reduced heat induction. As a result, micro-textured CVD diamond thick film cutting tools are also capable of machining high-performance materials due to reduced contact temperatures. In the scope of the research, the resulting temperature distribution for micro-textured rake faces will be compared under both dry and wet process conditions. Measurements show a reduction of the resulting cutting tool temperatures of Δϑt = 27.9 % using micro-textured cutting tools compared to non-textured cutting tools. A validated simulation provides valuable information about the contact temperatures enabling a specific development of the micro-texture geometry. As a result, a reduction of the contact temperature between chip and rake face by ΔϑT = 24.7 % was possible.