Fraunhofer-Institut für Produktionsanlagen und Konstruktionstechnik IPK

Filters
Reset filters

Settings
Now showing 1 - 8 of 8
  • Publication
    KI zur Prozessüberwachung im Unterpulverschweißen
    ( 2024-01-15)
    El-Sari, Bassel
    ;
    Gook, Sergej
    ;
    Biegler, Max
    ;
    Rethmeier, Michael
    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.
  • Publication
    Investigation of the LME Susceptibility of Dual Phase Steel with Different Zinc Coatings
    ( 2023-05-05)
    El-Sari, Bassel
    ;
    Biegler, Max
    ;
    Rethmeier, Michael
    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 spotwelded 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.
  • 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
    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
    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
    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
    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.