TY - JOUR A1 - Gook, S. A1 - El-Sari, B. A1 - Biegler, M. A1 - Rethmeier, Michael A1 - Lichtenthäler, F. A1 - Stark, M. T1 - Multiple-wire submerged arc welding of high-strength fine-grained steels N2 - Ensuring the required mechanical-technological properties of welds is a critical issue in the application of multi-wire submerged arc welding processes for welding high-strength fine-grained steels. Excessive heat input is one of the main causes for microstructural zones with deteriorated mechanical properties of the welded joint, such as a reduced notched impact strength and a lower structural robustness. A process variant is proposed which reduces the weld volume as well as the heat input by adjusting the welding wire configuration as well as the energetic parameters of the arcs, while retaining the advantages of multiwire submerged arc welding such as high process stability and production speed. KW - Submerged arc welding KW - High-strength fine-grained steels KW - Mechanical properties of the joints KW - Energy parameters of the arc PY - 2022 DO - https://doi.org/10.37434/tpwj2022.01.02 SN - 0957-798X IS - 1 SP - 9 EP - 13 PB - Paton Publishing House CY - Kiev AN - OPUS4-54701 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Raute, J. A1 - Biegler, M. A1 - Rethmeier, Michael T1 - Untersuchung zur Herstellung von Cu-Strukturen mittels Wire Electron Beam Additive Manufacturing N2 - Das Additive Manufacturing gewinnt zunehmend an Bedeutung für die Fertigung metallischer Bauteile im industriellen Umfeld. Hierbei wird zunehmend auch auf drahtförmige Ausgangswerkstoffe gesetzt, da diese Vorteile im Handling bieten, bereits in der Industrie etabliert sind und sich in der Regel durch geringere Beschaffungskosten auszeichnen. In den letzten Jahren entwickelte sich neben den bereits im großen Umfeld untersuchten Wire-DED-Verfahren auch eine Prozessvariante unter Nutzung des Elektronenstrahls zur industriellen Marktreife. Dabei zeigt die als Wire Electron Beam Additive Manufacturing bezeichnete Technologie besondere Vorteile gegenüber anderen, zumeist Laser- oder Lichtbogen-basierten DED-Prozessen. Das Verfahren bietet vor allem Potenzial für die Verarbeitung von hochleitfähigen, reflektierenden oder oxidationsgefährdeten Werkstoffen. Insbesondere für die Herstellung von Bauteilen aus Kupferlegierungen zeigt sich der Elektronenstrahl als besonders geeignet. Um das Verfahren einem breiten Anwenderkreis in der Industrie zugänglich zu machen, fehlen jedoch übergreifende Daten zu Leistungsfähigkeit, Prozessgrenzen und Anwendungsmöglichkeiten. Die vorliegende Untersuchung beschäftigt sich mit dieser Problemstellung am Beispiel zweier Cu-Werkstoffe. Dabei werden ein korrosionsbeständiger Werkstoff aus dem maritimen Bereich sowie eine Bronze mit guten Verschleißeigenschaften aus dem Anlagenbau getestet. Über mehrstufige Testschweißungen wurden die physikalisch möglichen Prozessgrenzen ermittelt und Rückschlüsse über die Eignung der Parameter zum additiven Aufbau gezogen. Hierfür wurden zunächst optimale Bereiche für den Energieeintrag anhand von Volumenenergie sowie mögliche Schweißgeschwindigkeiten untersucht. Anschließend wurde die Skalierbarkeit des Prozesses anhand von Strahlstrom und Drahtvorschub getestet. Als wesentliche Zielgrößen wurden dabei Spurgeometrie, Aufmischung und Härte herangezogen. Die Eignung der ermittelten Parameter wurde im letzten Schritt exemplarisch anhand einer additiven Testgeometrie in Form eines Zylinders nachgewiesen. T2 - DVS Congress 2022 Große Schweißtechnische Tagung DVS CAMPUS CY - Koblenz, Germany DA - 19.09.2022 KW - WEBAM KW - Electron beam KW - EBAM KW - Wire electron beam additive manufacturing PY - 2022 SN - 978-3-96144-189-1 VL - 382 SP - 446 EP - 454 PB - DVS Media AN - OPUS4-56058 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Kampffmeyer, D. A1 - Wolters, M. A1 - Raute, J. A1 - Biegler, M. A1 - Rethmeier, Michael T1 - Laserstrahlauftragschweißen – Einfluss von Schutzgasgemischen auf die Bauteilqualität N2 - Im Additive Manufacturing Verfahren Directed Energy Deposition (DED) wird bei der Verarbeitung von Werkzeugstahl in der Regel reines Argon als Schutzgas verwendet. Dabei kann die Verwendung von speziellen Schutzgasgemischen, auch bei geringen Anteilen zugemischter Gase, durchaus die Bauteilqualität positiv beeinflussen. In Vorarbeiten der Messer SE & Co. KGaA zeigte ein gewisser Sauerstoffanteil im Schutzgas die Tendenz, den Flankenwinkel von Schweißspuren beim DED zu verbessern. In der vorliegenden Studie wurde daher detailliert untersucht in wie weit unterschiedliche Schutzgasgemische einen Einfluss auf die Qualität sowie die geometrischen Eigenschaften der additiv gefertigten Strukturen des Werkzeugstahls 1.2709 beim Laser-DED ausüben. Es erfolgten zunächst Testschweißungen in Form von Einzelspuren mit unterschiedlichen Gemischen aus dem Basisschutzgas Argon mit geringen Anteilen verschiedener Gase. Dabei wurde der Einfluss der Zusätze auf die Spurgeometrie und Aufbauqualität untersucht. Auf Basis dieser Vorversuche wurde eine Auswahl vielversprechender Gasgemische getroffen und Detailuntersuchungen in Form von Spuren, Flächen und Quadern unter Zugabe verschiedener Mengen an Zusätzen durchgeführt. Zur Bewertung des Einflusses der Schutzgasbeimengungen wurden der Flankenwinkel, die Porosität und das Gefüge der Proben anhand metallografischer Schliffe untersucht. Es zeigte sich, dass eine Zugabe von geringen Anteilen an Zusätzen zunächst zu einer Vergrößerung des Flankenwinkels im Vergleich zu reinem Argon führt. Mit steigendem Anteil der Gase nimmt dieser Winkel jedoch ab. So kann je nach Menge des zugesetzten Gases eine individuelle Benetzung des aufgetragenen Materials an der Oberfläche erreicht werden. Auch die Porosität ließ sich durch Schutzgasgemische beeinflussen und zeigt ein abweichendes Verhalten im Vergleich zu reinem Argon. T2 - DVS Congress 2023 Große Schweißtechnische Tagung DVS CAMPUS CY - Essen, Germany DA - 11.09.2023 KW - Laser-Pulver-Auftragschweißen KW - DED-LB KW - Schutzgas KW - Additive Fertigung PY - 2023 SN - 978-3-96144-230-0 SP - 505 EP - 511 PB - DVS-Media AN - OPUS4-58585 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Raute, J. A1 - Marquardt, R. A1 - Biegler, M. A1 - Rethmeier, Michael T1 - Untersuchung zum Elektronenstrahlschweißen additiv gefertigter Ni-Basis-Bauteile N2 - Die vorliegende Untersuchung befasst sich mit dem Einfluss des Additive Manufacturing auf die Schweißeignung von Bauteilen aus Inconel 718. Hierfür wurden Proben mittels DED und L-PBF hergestellt und ihr Verhalten in Blindschweißversuchen anhand eines Vergleichs mit konventionellen Gussblechen untersucht. Im zweiten Schritt wurden die verschiedenen additiv hergestellten Proben mit dem Gussmaterial im I-Stoß sowie untereinander verschweißt. Als Schweißverfahren wurde für alle Proben das Elektronenstrahlschweißen angewandt. Zur Auswertung wurde anhand von Schliffen das Nahtprofil vermessen und die Proben auf Poren und Risse untersucht. Zusätzlich wurde die Dichte vermessen und eine Prüfung auf Oberflächenrisse durchgeführt. Das AM-Material zeigte dabei Unterschiede in Nahtform und Defektneigung im Vergleich zum Gusswerkstoff. Insbesondere die DED-proben neigten unter bestimmten Parameterkonstellationen verstärkt zu Porenbildung. Risse konnten nicht beobachtet werden. Trotz auftretender Nahtunregelmäßigkeiten wurde in den kombinierten AM-Schweißproben die Bewertungsgruppe C erreicht. Eine Prüfung der bestehenden Regelwerke zur Schweißnahtbewertung anhand der gewonnenen Erkenntnisse zu additiv gefertigten Proben im Elektronenstrahlschweißprozess zeigte keinen Ergänzungsbedarf. T2 - #additivefertigung: Metall in bestForm CY - Essen, Germany DA - 26.10.2022 KW - Elektronenstrahlschweißen KW - Additive Fertigung KW - Schweißnahtbewertung PY - 2022 SN - 978-3-96144-202-7 VL - 383 SP - 81 EP - 92 PB - DVS-Media GmbH AN - OPUS4-56173 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Marko, A. A1 - Bähring, S. A1 - Raute, J. A1 - Biegler, M. A1 - Rethmeier, Michael T1 - Transferability of ANN-generated parameter sets from welding tracks to 3D-geometries in Directed Energy Deposition N2 - 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. KW - Welding parameter KW - Quality assurance KW - DED KW - Artificial neural network KW - Additive manufacturing PY - 2022 DO - https://doi.org/10.1515/mt-2022-0054 SN - 0025-5300 VL - 64 IS - 11 SP - 1586 EP - 1596 PB - De Gruyter AN - OPUS4-56278 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Marko, A. A1 - Bähring, S. A1 - Raute, J. A1 - Biegler, M. A1 - Rethmeier, Michael T1 - Prognose von Qualitätsmerkmalen durch Anwendung von KI-Methoden beim Directed 10 Energy Deposition N2 - 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. KW - Kl KW - Directed Energy Depositio KW - Qualitätssicherung PY - 2022 SN - 0036-7184 VL - 74 IS - 10 SP - 672 EP - 679 PB - DVS Media CY - Düsseldorf AN - OPUS4-56284 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - El-Sari, B. A1 - Biegler, M. A1 - Rethmeier, Michael T1 - Investigation of the Extrapolation Capability of an Artificial Neural Network Algorithm in Combination with Process Signals in Resistance Spot Welding of Advanced High-Strength Steels N2 - Resistance spot welding is an established joining process for the production of safetyrelevant components in the automotive industry. Therefore, consecutive process monitoring is essential to meet the high quality requirements. Artificial neural networks can be used to evaluate the process parameters and signals, to ensure individual spot weld quality. The predictive accuracy of such algorithms depends on the provided training data set, and the prediction of untrained data is challenging. The aim of this paper was to investigate the extrapolation capability of a multi-layer perceptron model. That means, the predictive performance of the model was tested with data that clearly differed from the training data in terms of material and coating composition. Therefore, three multi-layer perceptron regression models were implemented to predict the nugget diameter from process data. The three models were able to predict the training datasets very well. The models, which were provided with features from the dynamic resistance curve predicted the new dataset better than the model with only process parameters. This study shows the beneficial influence of process signals on the predictive accuracy and robustness of artificial neural network algorithms. Especially, when predicting a data set from outside of the training space. KW - Automotive KW - Artificial intelligence KW - Quality monitoring KW - Resistance spot welding KW - Quality assurance PY - 2021 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-539783 DO - https://doi.org/10.3390/met11111874 VL - 11 IS - 11 SP - 1 EP - 11 PB - MDPI AN - OPUS4-53978 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Marko, A. A1 - Bähring, S. A1 - Raute, J. A1 - Biegler, M. A1 - Rethmeier, Michael T1 - Quality Prediction in Directed Energy Deposition Using Artificial Neural Networks Based on Process Signals N2 - The Directed Energy Deposition process is used in a wide range of applications including the repair, coating or modification of existing structures and the additive manufacturing of individual parts. As the process is frequently applied in the aerospace industry, the requirements for quality assurance are extremely high. Therefore, more and more sensor systems are being implemented for process monitoring. To evaluate the generated data, suitable methods must be developed. A solution, in this context, was the application of artificial neural networks (ANNs). This article demonstrates how measurement data can be used as input data for ANNs. The measurement data were generated using a pyrometer, an emission spectrometer, a camera (Charge-Coupled Device) and a laser scanner. First, a concept for the extraction of relevant features from dynamic measurement data series was presented. The developed method was then applied to generate a data set for the quality prediction of various geometries, including weld beads, coatings and cubes. The results were compared to ANNs trained with process parameters such as laser power, scan speed and powder mass flow. It was shown that the use of measurement data provides additional value. Neural networks trained with measurement data achieve significantly higher prediction accuracy, especially for more complex geometries. KW - DED KW - Artificial neural network KW - Process monitoring KW - Quality assurance KW - Data preparation PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-547039 DO - https://doi.org/10.3390/app12083955 VL - 12 IS - 8 SP - 1 EP - 13 PB - MDPI AN - OPUS4-54703 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Marko, A. A1 - Bähring, S. A1 - Raute, J. A1 - Biegler, M. A1 - Rethmeier, Michael T1 - Quality Prediction in Directed Energy Deposition Using Artificial Neural Networks Based on Process Signals N2 - The Directed Energy Deposition process is used in a wide range of applications including the repair, coating or modification of existing structures and the additive manufacturing of individual parts. As the process is frequently applied in the aerospace industry, the requirements for quality assurance are extremely high. Therefore, more and more sensor systems are being implemented for process monitoring. To evaluate the generated data, suitable methods must be developed. A solution, in this context, was the application of artificial neural networks (ANNs). This article demonstrates how measurement data can be used as input data for ANNs. The measurement data were generated using a pyrometer, an emission spectrometer, a camera (Charge-Coupled Device) and a laser scanner. First, a concept for the extraction of relevant features from dynamic measurement data series was presented. The developed method was then applied to generate a data set for the quality prediction of various geometries, including weld beads, coatings and cubes. The results were compared to ANNs trained with process parameters such as laser power, scan speed and powder mass flow. It was shown that the use of measurement data provides additional value. Neural networks trained with measurement data achieve significantly higher prediction accuracy, especially for more complex geometries. KW - DED KW - Artificial neural network KW - Data preparation KW - Quality assurance KW - Process monitoring PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-555063 DO - https://doi.org/10.3390/app12083955 SN - 2076-3417 VL - 12 IS - 8 SP - 1 EP - 13 PB - MDPI CY - Basel AN - OPUS4-55506 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Gook, S. A1 - Midik, A. A1 - Biegler, M. A1 - Gumenyuk, Andrey A1 - Rethmeier, Michael T1 - Joining 30 mm Thick Shipbuilding Steel Plates EH36 Using a Process Combination of Hybrid Laser Arc Welding and Submerged Arc Welding N2 - 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 SAWis carried out as a second run on the opposite side. With a SAWpenetration 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 HLAWroot; 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. KW - Shipbuilding steel KW - Hybrid laser arc welding KW - Submerged arc welding KW - Hardness KW - Bending test KW - Two-run welding technique KW - Microstructure PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-556090 DO - https://doi.org/10.3390/jmmp6040084 SN - 2504-4494 VL - 6 IS - 4 SP - 1 EP - 11 PB - MDPI CY - Basel AN - OPUS4-55609 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Brunner-Schwer, C. A1 - Simón Muzás, Juan A1 - Biegler, M. A1 - Hilgenberg, Kai A1 - Rethmeier, Michael T1 - Laser Welding of L-PBF AM components out of Inconel 718 N2 - With regard to efficient production, it is desirable to combine the respective advantages of additively and conventionally manufactured components. Particularly in the case of large-volume components that also include filigree or complex structures, it makes sense to divide the overall part into individual elements, which afterwards have to be joined by welding. The following research represents a first step in fundamentally investigating and characterizing the joint welding of Laser Powder Bed Fusion (L-PBF) components made of Inconel 718. For this purpose, bead-on-plate welds were performed on plates manufactured using the L-PBF process and compared with the conventionally manufactured material. Conventional laser beam welding was used as welding process. The weld geometry was investigated as a function of the L-PBF build-up orientation. It was found that the welding depth and weld geometry differ depending on this orientation and in comparison to the conventional material. T2 - 12th CIRP Conference on Photonic Technologies [LANE 2022] CY - Fürth, Germany DA - 04.09.2022 KW - Laser Welding KW - L-PBF KW - PBF-LB/M KW - Seam geometry KW - Bead-on-plate welds PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-560012 DO - https://doi.org/10.1016/j.procir.2022.08.072 SN - 2212-8271 VL - 111 SP - 92 EP - 96 PB - Elsevier B.V. AN - OPUS4-56001 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Lemke, J. A1 - Biegler, M. A1 - Rethmeier, Michael T1 - Fließfähigkeitsanalyse zweier Pulverfraktionen aus AISI 316L und resultierende Bauteildichte DED-LB aufgebauter Quader N2 - Die Fließfähigkeit von Metallpulvern gilt als wichtige Pulvereigenschaft für den additiven Aufbau mittels Laser, wobei bisher wenige Arbeiten die Auswirkungen im Laserpulverauftragschweißen (Engl.: Directed Energy Deposition DED-LB) untersuchen. Arbeiten, die sich mit den Pulvereigenschaften für Pulverbettverfahren beschäftigen, zeigen Korrelationen zwischen Partikelgrößenverteilung und Fließeigenschaften mit der Bauteildichte und den mechanischen Eigenschaften. Sie bewerten insbesondere Pulverbettdichte und -stabilität. In der vorliegenden Arbeit werden daher die Eigenschaften zweier Pulverfraktionen (20 µm – 63 µm und 63 µm – 150 µm) des austenitischen Stahls AISI 316L und deren freien Ausfluss im Vergleich zur Pulverdichte untersucht. Die Untersuchungen zeigen, dass die feinere Pulverfraktion eine um 14,5 % höhere Durchflussrate erzielt als die gröbere Fraktion. korreliert die Ergebnisse zur inneren Porosität und Partikelgrößenverteilung. Die Analyse der Bauteilqualität zeigt einen geringen Einfluss der Korngrößenverteilung auf die Porosiät der DED-LB aufgebauten Quader. T2 - 44. Assistentenseminar Fügetechnik der WGF CY - Päwesin, Germany DA - 20.09.2023 KW - 316L KW - Fließfähigkeit KW - DED-LB KW - Hall-Flow KW - Metallpulver PY - 2024 SP - 131 EP - 140 AN - OPUS4-60723 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Biegler, M. A1 - Rethmeier, Michael T1 - Numerische Simulation im 3D-Druck N2 - Die numerische Simulation hilft, Probleme bei additiven Bauprozessen früh zu erkennen und Optimierungspotentiale auszuschöpfen. Ziel ist, im additiven Auftragschweißen (DED) die Zahl der nötigen Versuche durch Vorhersagen zu verringern und Prozessgrößen zu visualisieren. Eine besondere Anwendung der Simulation ist die Generierung verzugskompensierter Geometrien: Durch die Berechnung des Bauteilverzugs kann die Geometrie vor dem Bauen so verändert werden, dass sie mit Verzug die gewünschte Toleranz erreicht. So kann Zerspanvolumen und Aufmaß reduziert werden. KW - Schweißsimulation KW - FEM KW - Auftragschweißen KW - Additive Fertigung KW - Verzug PY - 2020 IS - 4 SP - 45 EP - 48 AN - OPUS4-51097 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Biegler, M. A1 - Graf, B. A1 - Rethmeier, Michael T1 - Assessing the predictive capability of numerical additive manufacturing simulations via in-situ distortion measurements on a LMD component during build-up N2 - Due to rapid, localized heating and cooling, distortions accumulate in additive manufactured laser metal deposition (LMD) components, leading to a loss of dimensional accuracy or even cracking. Numerical welding simulations allow the prediction of these deviations and their optimization before conducting experiments. To assess the viability of the simulation tool for the use in a predictive manner, comprehensive systems as well as to choose the optimal product matches, product analysis methods are needed. Indeed, most of the known methods aim to analyze a product or one product family on the physical level. Different product families, however, may differ largely in terms of the number and nature of components. This fact impedes an efficient comparison and choice of appropriate product family combinations for the production system. A new methodology is proposed to analyze existing products in view of their functional and physical architecture. The aim is to Cluster these products in new assembly oriented product families for the optimization. KW - Laser metal deposition KW - Directed Energy Deposition KW - DED KW - Welding Simulation KW - Digital Image Correlation KW - Cimensional Accuracy PY - 2018 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-502567 DO - https://doi.org/10.1016/j.procir.2018.08.069 VL - 74 SP - 158 EP - 162 PB - Elsevier AN - OPUS4-50256 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - El-Sari, B. A1 - Biegler, M. A1 - Graf, B. A1 - Rethmeier, Michael T1 - Distortion-based validation of the heat treatment simulation of Directed Energy Deposition additive manufactured parts N2 - Directed energy deposition additive manufactured parts have steep stress gradients and an anisotropic microstructure caused by the rapid thermo-cycles and the layer-upon-layer manufacturing, hence heat treatment can be used to reduce the residual stresses and to restore the microstructure. The numerical simulation is a suitable tool to determine the parameters of the heat treatment process and to reduce the necessary application efforts. The heat treatment simulation calculates the distortion and residual stresses during the process. Validation experiments are necessary to verify the simulation results. This paper presents a 3D coupled thermo-mechanical model of the heat treatment of additive components. A distortion-based validation is conducted to verify the simulation results, using a C-ring shaped specimen geometry. Therefore, the C-ring samples were 3D scanned using a structured light 3D scanner to compare the distortion of the samples with different post-processing histories. KW - Directed Energy Deposition KW - Additive Manufacturing KW - Heat Treatment KW - Numerical Simulation KW - Finite Element Method PY - 2020 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-513153 DO - https://doi.org/10.1016/j.procir.2020.09.146 VL - 94 SP - 362 EP - 366 PB - Elsevier B.V. AN - OPUS4-51315 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Biegler, M. A1 - Wang, J. A1 - Kaiser, L. A1 - Rethmeier, Michael T1 - Automated Tool-Path Generation for Rapid Manufacturing of Additive Manufacturing Directed Energy Deposition Geometries N2 - In additive manufacturing (AM) directed energy deposition (DED), parts are built by welding layers of powder or wire feedstock onto a substrate with applications for steel powders in the fields of forging tools, spare parts, and structural components for various industries. For large and bulky parts, the choice of toolpaths influences the build rate, the mechanical performance, and the distortions in a highly geometry-dependent manner. With weld-path lengths in the range of hundreds of meters, a reliable, automated tool-path generation is essential for the usability of DED processes. This contribution presents automated tool-path generation approaches and discusses the results for arbitrary geometries. Socalled “zig-zag” and “contour-parallel” processing strategies are investigated and the tool-paths are automatically formatted into machine-readable g-code for experimental validation to build sample geometries. The results are discussed in regard to volume-fill, microstructure, and porosity in dependence of the path planning according to photographs and metallographic cross-sections. KW - Porosity KW - Path planning KW - Mechanical properties KW - Laser metal deposition KW - Additive manufacturing PY - 2020 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-510454 DO - https://doi.org/10.1002/srin.202000017 VL - 91 IS - 11 SP - 2000017 PB - WILEY-VCH Verlag GmbH & co. KGaA CY - Weinheim AN - OPUS4-51045 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Raute, J. A1 - Biegler, M. A1 - Rethmeier, Michael T1 - Process Setup and Boundaries of Wire Electron Beam Additive Manufacturing of High-Strength Aluminum Bronze N2 - In recent years, in addition to the commonly known wire-based processes of Directed Energy Deposition using lasers, a process variant using the electron beam has also developed to industrial market maturity. The process variant offers particular potential for processing highly conductive, reflective or oxidation-prone materials. However, for industrial usage, there is a lack of comprehensive data on performance, limitations and possible applications. The present study bridges the gap using the example of the high-strength aluminum bronze CuAl8Ni6. Multi-stage test welds are used to determine the limitations of the process and to draw conclusions about the suitability of the parameters for additive manufacturing. For this purpose, optimal ranges for energy input, possible welding speeds and the scalability of the process were investigated. Finally, additive test specimens in the form of cylinders and walls are produced, and the hardness profile, microstructure and mechanical properties are investigated. It is found that the material CuAl8Ni6 can be well processed using wire electron beam additive manufacturing. The microstructure is similar to a cast structure, the hardness profile over the height of the specimens is constant, and the tensile strength and elongation at fracture values achieved the specification of the raw material. KW - Wire electron beam additive manufacturing KW - Aluminum bronze KW - Wire-based additive manufacturing KW - EBAM KW - DED-EB PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-580890 DO - https://doi.org/10.3390/met13081416 VL - 13 IS - 8 SP - 1 EP - 16 PB - MDPI AN - OPUS4-58089 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - El-Sari, B. A1 - Biegler, M. A1 - Rethmeier, Michael T1 - Investigation of the LME Susceptibility of Dual Phase Steel with Different Zinc Coatings N2 - The application of anti-corrosion coated, high-strength steels in the automotive industry has increased in recent years. In combination with various zinc-based surface coatings, liquid metal embrittlement cracking can be observed in some of these materials. A high-quality, crack-free spot-welded joint is essential to realize the lightweight potential of the materials. In this work, the LME susceptibility of different coatings, which will be determined by the crack length and the occurrence rate, will be investigated using a welding under external load setup. The uncoated specimens did not show any LME. EG, GI and GA showed significantly less LME than ZM coatings. The latter coatings showed much larger crack lengths than the EG, GI and GA coatings. Furthermore, two mechanisms regarding the LME occurrence rate were observed: the occurrence of LME in zinc–magnesium coatings was theorized to be driven by the material properties of the coatings, whereas the occurrence of LME at EG, GI and GA samples was forced mainly by the application of the external tensile load. In the experimental setup of this work, the materials were exposed to unusually high mechanical loads (up to 80% of their yield strength) to evoke LME cracks. KW - Widerstandspunktschweißen KW - Hochfester Stahl KW - Liquid Metal Embrittlement KW - Flüssigmetallinduzierte Rissbildung KW - Zink KW - AHSS PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-580428 DO - https://doi.org/10.3390/met13050890 VL - 13 IS - 5 SP - 1 EP - 11 PB - MDPI AN - OPUS4-58042 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Yang, K. A1 - Meschut, G. A1 - Seitz, G. A1 - Biegler, M. A1 - Rethmeier, Michael T1 - The Identification of a New Liquid Metal Embrittlement (LME) Type in Resistance Spot Welding of Advanced High Strength Steels on Reduced Flange Widths N2 - Liquid metal embrittlement (LME) cracking is a phenomenon observed during resistance spot welding (RSW) of zinc􀀀coated advanced high􀀀strength steels (AHSS) in automotive manufacturing. In this study, severe cracks are observed at the edge of the sheet under reduced flange widths. These cracks, traversing the AHSS sheet, culminate at the edge with a width of approximately 1.2 mm. Through combined numerical and experimental investigations, and material testing, these cracks are identified and validated as a new type of LME crack. The mechanism behind this crack formation is attributed to unique geometric conditions that, when compared to center welding, amplify radial material flow by ninefold to 0.87 mm. The resultant tangential tensile stresses approximate 760 MPa, which exceed the yield strength of the examined advanced high􀀀strength steel (AHSS) under heightened temperature conditions, and when combined with liquid zinc, promote the formation of this new type of LME crack. KW - Liquid metal embrittlement KW - Crack KW - Advanced high strength steels KW - Resistance spot welding KW - Simulation KW - Flange width PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-586940 DO - https://doi.org/10.3390/met13101754 VL - 13 IS - 10 SP - 1 EP - 13 PB - MDPI AN - OPUS4-58694 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Marquardt, R. A1 - Biegler, M. A1 - Rethmeier, Michael T1 - Functionally graded material for improved wear resistance manufactured by directed energy deposition N2 - Protecting components against wear and corrosion is a common way to improve their lifetime. This can be achieved by coating them with a hardfacing material. Common coatings consist of materials such as tungsten carbide or cobalt-chromium alloys, also known as Stellite. Hardfacing materials can be deposited by welding methods like plasma welding or laser cladding. The discrete change of the base material to the hardfacing layer can lead to cracks and chipping. Studies showed a reduced risk of cracking when a functionally graded material is used to create a smooth transition between the base and the hardfacing. Gradings from austenitic steel to cobalt-chromium alloys are already known in the literature. However, there is no knowledge about austenitic- ferritic duplex steels as base material. Therefore, this study aims to demonstrate the feasibility of a functionally graded material from duplex steel to cobalt-chromium alloy with a new approach. By using powder-based directed energy deposition, a graded material with smooth material transition is manufactured additively. Cracking and porosity are examined through metallography. Microhardness measurements as well as the analysis of the chemical composition by energy dispersive X-ray spectroscopy and X-ray fluorescence are used to validate the build-up strategy. KW - Additive manufacturing KW - Functionally graded material KW - Functionally graded additive manufacturing KW - Directed energy deposition KW - Laser metal deposition PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-621683 DO - https://doi.org/10.1007/s40964-024-00879-4 SP - 1 EP - 6 PB - Springer Science and Business Media LLC AN - OPUS4-62168 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -