Fraunhofer-Institut für Produktionsanlagen und Konstruktionstechnik IPK

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  • Publication
    Багатодротове дугове зварювання високоміцних дрібнозернистих сталей під флюсом
    ( 2022)
    Gook, Sergej
    ;
    El-Sari, Bassel
    ;
    Biegler, Max
    ;
    Rethmeier, Michael
    ;
    Lichtenthäler, F.
    ;
    Stark, M.
    Ensuring the required mechanical-technological properties of welds is a critical issue in the application of multi-wire submerged arc welding process 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 multi-wire submerged arc welding such as high process stability and production speed
  • Publication
    Multiple-Wire Submerged Arc Welding of High-Strength Fine-Grained Steels
    ( 2022)
    Gook, S.
    ;
    El-Sari, Bassel
    ;
    Biegler, Max
    ;
    Rethmeier, Michael
    ;
    Lichtenthäler, F.
    ;
    Stark, M.
    Ensuring the required mechanical-technological properties of welds is a critical issue in the application of multi-wire submerged arc welding process 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 multi-wire submerged arc welding such as high process stability and production speed.
  • Publication
    Effects on crack formation of additive manufactured Inconel 939 sheets during electron beam welding
    ( 2022)
    Raute, Julius
    ;
    Jokisch, Torsten
    ;
    Biegler, Max
    ;
    Rethmeier, Michael
    The potential of additive manufacturing for processing precipitation hardened nickel-base superalloys, such as Inconel 939 is considerable, but in order to fully exploit this potential, fusion welding capabilities for additive parts need to be explored. Currently, it is uncertain how the different properties from the additive manufacturing process will affect the weldability of materials susceptible to hot cracking. Therefore, this work investigates the possibility of joining additively manufactured nickel-based superalloys using electron beam welding. In particular, the influence of process parameters on crack formation is investigated. In addition, hardness measurements are performed on cross-sections of the welds. It is shown that cracks at the seam head are enhanced by welding speed and energy per unit length and correlate with the hardness of the weld metal. Cracking parallel to the weld area shows no clear dependence on the process variables that have been investigated, but is related to the hardness of the heat-affected zone.
  • Publication
    Verbesserung der Vorhersagegüte von künstlichen neuronalen Netzen zum Widerstandspunktschweißen durch Auswertung des dynamischen Widerstands
    ( 2021)
    El-Sari, Bassel
    ;
    Biegler, Max
    ;
    Rethmeier, Michael
    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.
  • Publication
    Schweißen unter Zug - LME-Eingangsprüfung für die Autoindustrie
    ( 2021)
    El-Sari, Bassel
    ;
    Biegler, Max
    ;
    Rethmeier, Michael
    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.
  • Publication
    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
    ( 2021)
    El-Sari, Bassel
    ;
    Biegler, Max
    ;
    Rethmeier, Michael
    Resistance spot welding is an established joining process for the production of safety-relevant 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.
  • Publication
    Geometric distortion-compensation via transient numerical simulation for directed energy deposition additive manufacturing
    ( 2020)
    Biegler, Max
    ;
    Elsner, B.A.M.
    ;
    Graf, B.
    ;
    Rethmeier, Michael
    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 distortion-compensated 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%.
  • Publication
    Distortion-based validation of the heat treatment simulation of Directed Energy Deposition additive manufactured parts
    ( 2020)
    El-Sari, Bassel
    ;
    Biegler, Max
    ;
    Graf, B.
    ;
    Rethmeier, Michael
    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.
  • Publication
    Finite element analysis of in-situ distortion and bulging for an arbitrarily curved additive manufacturing directed energy deposition geometry
    ( 2018)
    Biegler, Max
    ;
    Marko, Angelina
    ;
    Graf, Benjamin
    ;
    Rethmeier, Michael
    With the recent rise in the demand for additive manufacturing (AM), the need for reliable simulation tools to support experimental efforts grows steadily. Computational welding mechanics approaches can simulate the AM processes but are generally not validated for AM-specific effects originating from multiple heating and cooling cycles. To increase confidence in the outcomes and to use numerical simulation reliably, the result quality needs to be validated against experiments for in-situ and post process cases. In this article, a validation is demonstrated for a structural thermomechanical simulation model on an arbitrarily curved Directed Energy Deposition (DED) part: at first, the validity of the heat input is ensured and subsequently, the model's predictive quality for in-situ deformation and the bulging behaviour is investigated. For the in-situ deformations, 3D-Digital Image Correlation measurements are conducted that quantify periodic expansion and shrinkage as they occur. The results show a strong dependency of the local stiffness of the surrounding geometry. The numerical simulation model is set up in accordance with the experiment and can reproduce the measured 3 dimensional in-situ displacements. Furthermore, the deformations due to removal from the substrate are quantified via 3D scanning, exhibiting considerable distortions due to stress relaxation. Finally, the prediction of the deformed shape is discussed in regards to bulging simulation: to improve the accuracy of the calculated final shape, a novel extension of the model relying on the modified stiffness of inactive upper layers is proposed and the experimentally observed bulging could be reproduced in the finite element model.