Fraunhofer-Institut für Produktionsanlagen und Konstruktionstechnik IPK

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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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AI-based welding process monitoring for quality control in large-diameter pipe manufacturing

2024-04-25 , 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. In the spectrogram of the acoustic signal, which represents the time course of the frequency spectrum of the welding process, the formation of weld irregularities such as undercuts could be reliably identified. 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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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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Vom prozessorientierten Qualitätsmanagementsystem zum adaptiven Lernpfad

2024 , Orth, Ronald , Kretschmer, Maria , Singer-Coudoux, Katrin , Schmid, Robert

Verschiedene Rahmenwerke des Qualitätsmanagements betonen die Relevanz kompetenter Mitarbeiter:innen für den Unternehmenserfolg. Unternehmen müssen erfolgskritische Kompetenzen bestimmen und bewerten sowie Maßnahmen zur Kompetenzentwicklung umsetzen. Dieser Beitrag stellt einen Ansatz vor, der Unternehmen dabei unterstützt, anhand von prozessorientierten Skill-Profilen und einer KI-basierten Lernplattform diese Aufgaben zu bewerkstelligen. Im Mittelpunkt stehen dabei adaptive Lernpfade der Beschäftigten. Das Fallbeispiel der FBT Feinblechtechnik GmbH demonstriert die Anwendung des Ansatzes in der Praxis.

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Technologieaudit zur Bewertung von Forschungs- und Technologieorganisationen

2024-07-25 , Hecklau, Fabian

Forschungs- und Technologieorganisationen (RTOs) bilden die Brücke zwischen Grundlagenforschung und Industrie und sind somit zentrale Akteure nationaler Innovationssysteme. Um in einem dynamischen Forschungs- und Geschäftsumfeld konkurrenzfähig und langfristig erfolgreich sein zu können, müssen RTOs innovative technologische Lösungen anbieten. Diese Innovationen können sie nur generieren, wenn sie präzise Kenntnis über die eigenen technologischen Stärken und Schwächen erlangen. Das Technologieaudit bildet eine Methode, die es erlaubt, die technologische Reife von Forschungs- und Technologieorganisationen systematisch zu analysieren und zu bewerten, Verbesserungspotenziale zu identifizieren und Optimierungsprozesse anzustoßen. Die Arbeit nimmt eine umfassende Untersuchung vor, um mithilfe des Methoden-Engineerings diese passgenaue, standardisierte und umsetzungsorientierte Methode zur technologischen Auditierung von RTOs zu entwerfen und in der praktischen Anwendung zu prüfen.

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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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Flexibles AM ermöglicht wettbewerbsfähige Produktion

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

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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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Investigation on stereo-ToF data fusion for the inspection of used industrial parts

2024 , Krumpek, Oliver , Schlüter, Marian , Hügle, Johannes

Optical systems for automated or partially automated inspection have been making important contributions to ensure the quality and functionality of technical products for many years. Often used to monitor the quality of newly produced goods, vision systems also aim to play an important role in identification and condition description of used industrial parts such as aged vehicle components. In this work, a passive stereo system and a Time-of-Flight (ToF) sensor of the latest generation were used to create the desired sensor system. In the first step, the pixel-based information of both sensors was exploited to spatially calibrate the transformation between the left stereo camera and the ToF sensor by forming a 2D-3D correspondence set of detected feature points. To compensate for the resolution difference of the sensors, numerous interpolation points were randomly sampled on the reconstructed sparse surface mesh of the ToF sensor to create the missing sub-pixel information. It could be shown that the fused sensor information led to an increase in incompleteness by 7.81% on average for all components examined. The higher noise in the ToF measurement data in the fill-ins could be mitigated by using an adapted median kernel filtering. The average deviation of the measurement from a reference dataset was 1.30mm for the stereo system, 2.51mm for the ToF system, and 1.42mm for the fused result. The result of this work is promising as the quality of the surface mesh could be raised especially for critical surface areas and the underlying RGB data itself can be used for pixel-wise classification and segmentation.

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