Fraunhofer-Institut für Produktionsanlagen und Konstruktionstechnik IPK

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Energieeffizienzsteigerung mit IoT-basiertem Monitoringsystem

2024-09-22 , Uhlmann, Eckart , Polte, Julian , Geisert, Claudio

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Flexibles AM ermöglicht wettbewerbsfähige Produktion

2024-05 , Müller, Vinzenz , Fasselt, Janek Maria , Klötzer-Freese, Christian , Kruse, Tobias , Wagner, Florian

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Numerical and experimental assessment of liquid metal embrittlement in externally loaded spot welds

2024-01-30 , Prabitz, Konstantin , Antretter, Thomas , Rethmeier, Michael , El-Sari, Bassel , Schubert, Holger , Hilpert, Benjamin , Gruber, Martin , Sierlinger, Robert , Ecker, Werner

Zinc-based surface coatings are widely applied with high-strength steels in automotive industry. Some of these base materials show an increased brittle cracking risk during loading. It is necessary to examine electrogalvanized and uncoated samples of a high strength steel susceptible to liquid metal embrittlement during spot welding with applied external load. Therefore, a newly developed tensile test method with a simultaneously applied spot weld is conducted. A fully coupled 3D electrical, thermal, metallurgical and mechanical finite element model depicting the resistant spot welding process combined with the tensile test conducted is mandatory to correct geometric influences of the sample geometry and provides insights into the sample’s time dependent local loading. With increasing external loads, the morphology of the brittle cracks formed is affected more than the crack depth. The validated finite element model applies newly developed damage indicators to predict and explain the liquid metal embrittlement cracking onset and development as well as even ductile failure.

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Collision detection for collaborative assembly operations on high-payload robots

2024 , Katsampiris-Salgado, Konstantinos , Haninger, Kevin , Gkrizis, Christos , Dimitropoulos, Nikos , Krüger, Jörg , Michalos, George A. , Makris, Sotiris

Human-robot collaboration for high-payload industrial applications has the potential to unlock new applications and improve operator ergonomics. However, ensuring safety with closer proximity remains challenging due to the large payload. Collision detection can improve safety, but must be modified to consider the dynamics of high payload applications (internal oscillation, effective low-pass filtering of external force), while the higher inertia raises questions about the resulting collision forces. This paper proposes the first collision detection approach for high-payload applications, using a force/torque sensor at the end-effector and motor current measurements for redundancy to be compliant with ISO/TS 15066:2016. Analysis of a linear model informs the design of the detection algorithm and effect of higher payload. Experimental validation shows feasibility and performance of collision detection over a range of motion and payload conditions, and the impact of the safety system in improving an industrial use-case.

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Detektion von Bindefehlern beim DED-Arc

2024-08 , Neumann, Benedikt Bog Man , Biegler, Max , Goecke, Sven-Frithjof , Rethmeier, Michael

In dem Beitrag wird aufbauend auf Machine-Learning-Modellen, welche bereits zum Überwachen des Schutzgasschweißen erforscht wurden, ein tiefes neuronales Netz (DNN) zum Monitoring beim DED-Arc von Aluminium vorgestellt. Ziel ist die Detektion von Bindefehlern in den aufgebauten Volumina auf Grundlage von in Echtzeit gemessenen Schweißstromquellensignalen. Es werden Merkmalsvariablen durch Vorverarbeitung extrahiert sowie die Korrelation zwischen den Merkmalsvariablen und den Defekten analysiert. Durch den vorgestellten Algorithmus werden diese automatisiert als Input an ein DNN übergeben. Das entwickelte und trainierte neuronale Netz erkennt anhand signifikanter Merkmale aus den Strom- und Spannungsdaten Bindefehler mit einer Genauigkeit von ca. 90 Prozent.

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Digital Twins within the Circular Economy: Literature Review and Concept Presentation

2024-03-26 , Mügge, Janine , Seegrün, Anne , Hoyer, Tessa-Katharina , Riedelsheimer, Theresa , Lindow, Kai

Digital twins offer a promising approach to sustainable value creation by providing specific life cycle data and enabling the monitoring and implementation of circular economy strategies throughout the product’s life cycle. By analyzing product, component, and material data, as well as process data, it is possible to create transparency throughout a product’s life cycle, build a data-driven product ecosystem, and establish new business and value creation models, from SMEs to large enterprises. This paper identifies application scenarios, their technological readiness level, and the challenges of digital twins for the circular economy in the manufacturing industry based on a systematic literature review. Gaps such as ensuring a continuous flow of information and taking into account the different levels of digitalization of companies are identified. As a main result, a holistic concept for the scoping of a digital twin for the circular economy is presented. One specific use case for end-of-life decision-making is elaborated upon. It is shown that the circular economy can be supported by digital twin data, especially for the optimal decision on end-of-life vehicles.

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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.

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Application of AI-based welding process monitoring for quality control in pipe production

2024-07-29 , Gook, Sergej , El-Sari, Bassel , Biegler, Max , Rethmeier, Michael

The paper presents the experimental results into the development of a multi-channel system for monitoring and quality assurance of the multi-wire submerged arc welding (SAW) process for the manufacture of large diameter pipes. Process signals such as welding current, arc voltage and the acoustic signal emitted from the weld zone are recorded and processed to provide information on the stability of the welding process. It was shown by the experiments that the acoustic pattern of the SAW process in a frequency range between 30 Hz and 2.5 kHz contains the most diagnostic information. The on-line quality assessment of the weld seam produced is carried out in combination with methods of artificial intelligence (AI). From the results obtained, it can be concluded that the use of the latest concepts in welding and automation technology, combined with the high potential of AI, can achieve a new level of quality assurance in pipe manufacturing.

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Qualitätssicherung beim Laser-Pulver-Auftragschweißen

2024-02-01 , Lemke, Josefine

In der modernen Fertigungstechnik spielt der Einsatz von korrosionsbeständigem Stahl eine große Rolle. Die kohlenstoffarme Edelstahllegierung 1.4404 (AISI 316L) ist ein häufig eingesetzter Werkstoff in der additiven Fertigung. Hier kann das Laser-Pulver-Auftragschweißen (LPA), engl. Directed Energy Deposition DED-LB, das weit verbreitete Laser Powder Bed Fusion (L-PBF) aufgrund höherer Auftragsraten und seiner Flexibilität in einigen Bereichen ergänzen und sogar ersetzen. Mit interessanten Perspektiven in der Bremsscheibenfertigung für Automobile.

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New methodology for the characterization of 3D model reconstructions to meet conditions of input data and requirements of downstream applications

2024 , Joost, Robert , Mönchinger, Stephan , Lindow, Kai

In the field of 3D model reconstruction, manifold methods have been developed that derive CAD models from 3D scan data. Opposed to classical CAD modelling, where surface and solid modelling exist, a further diversification of modelling techniques is observed, caused by different methods to build up the geometry. This research introduces a new classification, the so-called Level of Complexities. It can be applied to the complete Reverse Engineering process chain and lays the foundation for further research on how to match requirements arising from all process steps and downstream applications.

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