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PublicationDetektion von Bindefehlern beim DED-Arc( 2024-08)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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PublicationApplication of AI-based welding process monitoring for quality control in pipe production( 2024-07-29)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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PublicationDigital Twins within the Circular Economy: Literature Review and Concept Presentation( 2024-03-26)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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PublicationQualitätssicherung beim Laser-Pulver-Auftragschweißen( 2024-02-01)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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PublicationNumerical and experimental assessment of liquid metal embrittlement in externally loaded spot welds( 2024-01-30)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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PublicationKI zur Prozessüberwachung im Unterpulverschweißen( 2024-01-15)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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PublicationIncorporating sustainability into product lifecycle management: a systematic literature review( 2024)Amidst environmental, regulatory, and societal pressures, integrating sustainability into Product Lifecycle Management (PLM) is key, evolving into Sustainable PLM (sPLM). This paper uses a systematic literature review and text-mining (C-value method) to categorise sPLM research into clusters, assess their integration at organisational levels, and evaluate the level’s maturity. Findings highlight a gap in operational sPLM research. Future studies should bridge the gap between theory and industrial application, enhance sPLM operationalisation, and explore emerging technologies’ impact on sPLM.
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PublicationEffect of the heat treatment on the microstructure of carbide tool electrodes for electrical discharge drilling( 2024)Carbide tool electrodes for electrical discharge drilling were subjected to heat treatment at various temperatures and in different atmospheres for the same duration, respectively, in order to reduce the electrical conductivity of the lateral surface. Hardness tests show that the heat treatment does not induce a loss of strength in the electrode body. Microscopic analyses revealed that the lateral surface, characterized by a two-layer structure comprising a surface and a diffusion layer of varying characteristics and morphology, such as surface roughness, degree of coverage, delaminations, or a columnar microstructure, changes. It is revealed that the electrical conductivity is a function of the total layer thickness made up of the thickness of the surface layer and a diffusion layer. The electrical conductivity drops with increasing total layer thickness. In the context of electric discharge drilling tests, it was found that the reduced electrical conductivity leads to a decreased material removal rate and a simultaneously reduced linear electrode wear. Heat treatments ensuring consistent erosion times resulted in a wear rate reduction of the tool electrodes of up to 10 %.
