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Der Trend zum Leichtbau und die Transformation zur E-Mobilität in der
Automobilindustrie befeuern die Entwicklung neuer hochfester Stähle für den Karosseriebau. Derartige Werkstoffe sind beim Widerstandspunktschweißen besonders rissanfällig (LME). Das Schweißen unter Zug stellt eine effektive Methode um die LME-Anfälligkeit unterschiedlicher Werkstoffe qualitativ zu bestimmen.
Components distort during directed energy deposition (DED) additive manufacturing (AM) due to the repeated localised heating. Changing the geometry in such a way that distortion causes it to assume the desired shape – a technique called distortion-compensation – is a promising method to reach geometrically accurate parts. Transient numerical simulation can be used to generate the compensated geometries and severely reduce the amount of necessary experimental trials. This publication demonstrates the simulation-based generation of a distortioncompensated DED build for an industrial-scale component. A transient thermo-mechanical approach is extended for large parts and the accuracy is demonstrated against 3d-scans. The calculated distortions are inverted to derive the compensated geometry and the distortions after a single compensation iteration are reduced by over 65%.
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.
Distortions in Additive Manufacturing (AM) Laser Metal Deposition (LMD) occur in the newly-built component due to rapid heating and solidification and can lead to shape deviations and cracking. This paper presents a novel approach to quantify the distortions experimentally and to use the results in numerical simulation validation. Digital Image Correlation (DIC) is applied together with optical filters to measure in-situ distortions directly on a wall geometry produced with LMD. The wall shows cyclic Expansion and shrinking with the edges bending inward and the top of the sample exhibiting a slight u-shape as residual distortions. Subsequently, a structural Finite Element Analysis (FEA) of the experiment is established, calibrated against experimental temperature profiles and used to predict the in-situ distortions of the sample. A comparison of the experimental and numerical results reveals a good agreement in length direction of the sample and quantitative deviations in height direction, which are attributed to the material model used. The suitability of the novel experimental approach for measurements on an AM sample is shown and the potential for the validated numerical model as a predictive tool to reduce trial-and-error and improve part quality is evaluated.
Rapid localized heating and cooling during additive manufacturing using laser deposition method (LMD) lead to loss of dimensional accuracy as well as cracking of built parts. Finite-Element welding simulations allow prediction of geometrical deviations and accumulated residual stresses as well as their optimization before conducting experiments. Due to the great length of stacked welds, calculation times for fully transient thermomechanical simulations are currently long, the calculation stability suffers from the high number of contact bodies in the model and the modelling effort is high, as the geometries need to be sliced and positioned layer-wise.
In this contribution, an integrated modelling approach is demonstrated for a thin-walled LMD component made from 30 layers of 1.4404 (316L) stainless steel: Instead of the layer-by-layer modelling strategy commonly found in the literature, the whole component mesh is kept in one piece and the fully transient, layer-by-layer material deposition is implemented via element sets. In contrast to prior simulations, nonlinear contact between the layers does not have to be considered, significantly decreasing calculation times. The calculated distortions are compared to recently published, in-situ digital image correlation (DIC) measurements as well as numerical simulations conducted with the established layer-wise modelling strategy to judge result quality. Finally, the improvement in calculation time and ease-of-use is compared between both modelling approaches and conclusions regarding future usage for industrial-scale components are drawn.
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.
In additive manufacturing (AM) Laser Metal Deposition (LMD), parts are built by welding layers of powder feedstock onto a substrate. Applications for steel powders include forging tools and structural components for various industries. For large parts, the choice of tool-paths influences the build-rate, the part 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 LMD processes.
In this contribution, automated tool-path generation approaches are shown and their results are discussed for arbitrary geometries. The investigated path strategies are the classical approaches: “Zig-zag-” and “contour-parallel-strategies”. After generation, the tool-paths are automatically formatted into g-code for experimental build-up and ASCII for a numerical simulation model. Finally, the tool paths are discussed in regards to volume-fill, microstructure and porosity for the experimental samples.
This work presents a part of the IGF project 18737N “Welding distortion simulation” (FOSTA P1140)
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.
The contact between train wheels and rail tracks is known to induce material degradation in the form of wear, and rolling contact fatigue in the railhead. Rails with a pearlitic microstructure have proven to provide the best wear resistance under severe wheel-rail interaction in heavy haul applications. High speed laser cladding, a state-of-the-art surface engineering technique, is a promising solution to repair damaged railheads. However, without appropriate preheating or processing strategies, the utilized steel grades lead to martensite formation and cracking during deposition welding.
In this study, laser cladding of low-alloy steel at very high speeds was investigated, without preheating the railheads. Process speeds of up to 27 m/min and laser power of 2 kW are used. The clad, heat affected zone and base material are examined for cracks and martensite formation by hardness tests and metallographic inspections. A methodology for process optimization is presented and the specimens are characterized for suitability. Within the resulting narrow HAZ, the hardness could be significantly reduced.
During resistance spot welding of zinc-coated advanced high-strength steels (AHSSs) for automotive production, liquid metal embrittlement (LME) cracking may occur in the event of a combination of various unfavorable influences. In this study, the interactions of different welding current levels and weld times on the tendency for LME cracking in third-generation AHSSs were investigated. LME manifested itself as high penetration cracks around the circumference of the spot welds for welding currents closely below the expulsion limit. At the same time, the observed tendency for LME cracking showed no direct correlation with the overall heat input of the investigated welding processes. To identify a reliable indicator of the tendency for LME cracking, the local strain rate at the origin of the observed cracks was analyzed over the course of the welding process via finite element simulation. While the local strain rate showed a good correlation with the process-specific LME cracking tendency, it was difficult to interpret due to its discontinuous course. Therefore, based on the experimental measurement of electrode displacement during welding, electrode indentation velocity was proposed as a descriptive indicator for quantifying cracking tendency.
Advanced high strength steels are usually coated by a zinc layer for an increased resistance against corrosion. During the resistance spot welding of zinc coated steel grades, liquid metal embrittlement (LME)mayoccur. As a result, cracking inside and around the spot weld indentation is observable. The extent of LME cracks is influenced by a variety of different factors. In this study, the impact of the used electrode geometry is investigated over a stepwise varied weld time.
A spot welding finite element simulation is used to analyse and explain the observed effects. Results show significant differences especially for highly increased weld times. Based on identical overall dimensions, electrode geometries with a larger working plane allow for longer weld times, while still preventing LME within the investigated material and maintaining accessibility.
Liquid metal embrittlement (LME) cracking can occur during resistance spot welding (RSW) in zinc-coated advanced high-strength steels (AHSS) for automotive production. In this study, a methodological variation of hold time is performed to investigate the process-related crack influence factors. A combination of numerical and experimental investigations confirms, that the extent of heat dissipation and re-heating of the sheet surface can be influenced and thus the degree of crack formation can be controlled in a targeted manner by the parameterisation of the hold time. The temperature and stress history of crack-free and crack-afflicted spot welds are analysed and a conclusion on the borders defining the LME active region is derived.
Beim Unterpulverschweißen sind die Prozessgeräusche ein Indikator für eine gute Fügequalität. Diese Beurteilung kann i.d.R. nur von einer erfahrenen Fachkraft durchgeführt werden. Eine kürzlich entwickelte künstliche Intelligenz kann automatisch das akustische Prozesssignal anhand vortrainierter Merkmale klassifizieren und die Fügequalität anhand des Geräuschs beurteilen. Der Algorithmus, einmal richtig trainiert, kann den Prüfaufwand beim Unterpulverschweißen deutlich reduzieren.
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.
Das DED Auftragschweißen ist ein additives Fertigungsverfahren für Metalle, bei dem das Material schichtweise auf ein Substrat aufgetragen wird. Die schnellen Temperaturzyklen rufen Spannungsgradienten im Bauteil hervor. Der schichtweise Aufbau der Bauteile verursacht eine anisotrope Mikrostruktur. Mittels nachgelagerter Wärmebehandlung können diese Effekte verringert werden. Im anschließenden Schritt der Prozesskette wird das additiv hergestellte Bauteil mittels Drahterodieren von dem Substrat abgetrennt.
In diesem Beitrag wird eine thermo-mechanische Simulation der gesamten Prozesskette vorgestellt, welche den additiven Aufbau, Wärmebehandlung und das Abtrennen vom Substrat beinhaltet. Anstelle der in der Literatur üblichen schichtweisen Modellierungsstrategie für die DED Simulation wird das gesamte Bauteil in einem Stück vernetzt und der vollständig transiente, schichtweise Materialauftrag über Elementgruppen realisiert. Im Gegensatz zu früheren Simulationen muss der nichtlineare Kontakt zwischen den Schichten nicht berücksichtigt werden, was die Rechenzeiten deutlich verkürzt.
Das Modell wurde validiert mittels Abgleiches des Verzugs aus Simulation und Experiment.
Die Proben, bestehend aus DIN 1.4404 (AISI 316L), wurden nach jedem Prozessschritt 3D gescannt um den Verzug zu quantifizieren. Zusätzlich wurden Querschnitte und Härtetests nach Vickers von unterschiedlich behandelten Proben durchgeführt, um den Effekt der Wärmebehandlung auf die Mikrostruktur und die Härte des Bauteils zu untersuchen.
Das Widerstandspunktschweißen ist ein etabliertes Fügeverfahren in der Automobilindustrie. Es wird vor allem bei der Herstellung sicherheitsrelevanter Bauteile, zum Beispiel der Karosserie, eingesetzt. Daher ist eine kontinuierliche Prozessüberwachung unerlässlich, um die hohen Qualitätsanforderungen zu erfüllen. Künstliche neuronale Netzalgorithmen können zur Auswertung der Prozessparameter und -signale eingesetzt werden, um die individuelle Schweißpunktqualität zu gewährleisten. Die Vorhersagegenauigkeit solcher Algorithmen hängt von dem zur Verfügung gestellten Trainingsdatensatz ab. In diesem Beitrag wird untersucht, inwieweit die Vorhersagegüte eines künstlichen neuronalen Netzes durch Auswertung einer Prozessgröße, dem dynamischen Widerstand, verbessert werden kann.
Directed energy deposition is a metal additive manufacturing process that builds parts by joining material in a layer-by-layer fashion on a substrate. Those parts are exposed to rapid thermo-cycles which cause steep stress gradients and the layer-upon-layer manufacturing fosters an anisotropic microstructure, therefore stress relief heat treatment is necessary. The numerical simulation can be used to find suitable parameters for the heat treatment and to reduce the necessary efforts to perform an effective stress relieving. Suitable validation Experiments are necessary to verify the results of the numerical simulation.
In this paper, a 3D coupled thermo-mechanical model is used to simulate the heat treatment of an additive manufactured component to investigate the application of a C-ring geometry for the distortion-based validation of the numerical simulation.
Therefore, the C-ring samples were 3D scanned using a structured light 3D scanner to quantify the distortion after each process step.
Eine typische Automobilkarosserie kann bis zu 5000 Widerstandspunktschweißverbindungen aufweisen, welche hohen Qualitätsanforderungen genügen müssen. Daher ist eine durchgehende Prozessüberwachung unerlässlich. Die Transformation zur E-Mobilität in der Automobilindustrie und die damit einhergehende Reichweitenproblematik treiben die Entwicklung und Einführung neuer hochfester Stähle an. Dies resultiert in einem gesteigerten Fertigungsaufwand hinsichtlich einer stabilen Prozess-führung in der Fügetechnik. Um diesen Anstieg an Komplexität zu bewältigen, sind die Methoden der künstlichen Intelligenz ein geeignetes Mittel. Mit ihnen kann, durch Auswertung der Prozessparameter und -signale, die individuelle Schweißpunktqualität sichergesellt werden. Die Vorhersagegenauigkeit von neuen Daten, also das extrapolieren, stellt für die meisten Algorithmen eine große Herausforderung dar.
In dieser Arbeit wird ein künstliches neuronales Netz zur Vorhersage des Punktdurchmessers von Widerstandspunktschweißungen anhand von Prozessparametern implementiert. Die Vorhersagegenauigkeit und Extrapolationsfähigkeit des Modells wird durch die Auswertung des dynamischen Widerstandssignals verbessert.
Um die Extrapolationsfähigkeit zu untersuchen, wird die Vorhersagegenauigkeit des Modells mit Daten getestet, die sich in Bezug auf den Werkstoff und der Beschichtungszusammensetzung deutlich von den Trainingsdaten unterscheiden. Dazu wurden mehrere Schweißexperimente mit Werkstoffen verschiedener Hersteller durchgeführt und nur ein Teil der Daten in das Training einbezogen. Die Ergebnisse dieser Arbeit verdeutlichen den positiven Einfluss der Prozesssignale auf die Robustheit des Modells und die Skalierbarkeit der Algorithmen
künstlicher neuronaler Netze auf Daten außerhalb des Trainingsraums.
Die Beschichtung hochfester Stahlfeinbleche beeinflusst das Auftreten von flüssigmetallinduzierter Rissbildung (LME). Daher wurden in dieser Arbeit industrieübliche Beschichtungen bei gleichem Grundwerkstoff hinsichtlich ihres Aufbaus und chemischer Zusammensetzung charakterisiert und bezüglich ihrer LME Anfälligkeit untersucht. Aus dieser vergleichenden Untersuchung heraus wurden Potentiale für die Widerstandsfähigkeit gegen LME identifiziert. Diese Potentiale werden experimentell durch den Einsatz einer von der Forschungsstelle entwickelten Methode überprüft. Gegenstand der Untersuchungen waren neben unbeschichteten Proben industrieübliche Zinküberzüge wie Elektrolytisch verzinkt, Feuerverzinkt, Galvannealed und Zink-Magnesium Beschichtungen.
Die LME Anfälligkeit dieser unterschiedlichen Überzüge wird mit einem Schweißen unter Zugbelastung Versuchsaufbau untersucht. Dabei ergibt sich die resultierende Anfälligkeit aus den auftretenden Risslängen und der Auftrittswahrscheinlichkeit von LME bei den einzelnen Versuchen. Es konnte eine LME Anfälligkeits-Rangfolge für die Zinküberzüge festgestellt werden. Zink-Magnesium Beschichtungen galten als besonders LME Anfällig, gefolgt von Feuerverzinkt und Galvannealed. Die größte LME Resistenz wurde bei elektrolytisch verzinkten Proben festgestellt.
Aus den Ergebnissen werden Handlungsempfehlungen zur Erhöhung der Verarbeitungssicherheit bzw. Schweißpunktqualität abgeleitet.
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.