FSP3: Produktion
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Algorithms for causal discovery have recently undergone rapid advances and increasingly draw on flexible nonparametric methods to process complex data. With these advances comes a need for adequate empirical validation of the causal relationships learned by different algorithms. However, for most real and complex data sources true causal relations remain unknown. This issue is further compounded by privacy concerns surrounding the release of suitable high-quality data. To tackle these challenges, we introduce causalAssembly, a semisynthetic data generator designed to facilitate the benchmarking of causal discovery methods. The tool is built using a complex real-world dataset comprised of measurements collected along an assembly line in a manufacturing setting. For these measurements, we establish a partial set of ground truth causal relationships through a detailed study of the physics underlying the processes carried out in the assembly line. The partial ground truth is sufficiently informative to allow for estimation of a full causal graph by mere nonparametric regression. To overcome potential confounding and privacy concerns, we use distributional random forests to estimate and represent conditional distributions implied by the ground truth causal graph. These conditionals are combined into a joint distribution that strictly adheres to a causal model over the observed variables. Sampling from this distribution, causalAssembly generates data that are guaranteed to be Markovian with respect to the ground truth. Using our tool, we showcase how to benchmark several well-known causal discovery algorithms.
Wide bandgap semiconductors, SiC and GaN-based power devices represent key candidates in the development of more efficient devices due to their superior electrical and thermal properties compared to silicon. To achieve maximal performance from WBG semiconductors, new packaging technologies and thermo-electric designs must be developed to ensure efficient and fast switching of devices while minimizing losses. The paper aims to investigate the thermal and mechanical behavior of new prepackage embedding technologies by finite element simulation. The focus is on insulated substrates including direct bonded copper (DBC) with various dielectrics such as AlN, Al 2O 3, Si3N 4 and new insulated metal substrates (IMS) with emphasis on commercially available materials and thicknesses. This study proposes a thermo-mechanical pareto-optimization methodology able to identify the best substrate configuration. The sintered silver layer (in both sides of the chip), which is the most prone to failure due to delamination, has been modelled with a temperature-dependent bilinear hardening model to account for plasticity. Pareto-optimization accounts for the module thermal resistance and the plastic strain or Von Mises Stress in the sintered layer. Results demonstrate that the best candidate from the thermo-mechanical point of view is the DBC with AlN showing a thermal resistance of 0.34 K/W, accumulative plastic strain of 0.18 % and Von Mises stress of 274 MPa. Finally, the parasitic inductance of multiple pre-packages is evaluated to scale the power of the module. Proper design allows to achieve a stray inductance as small as 1.23 nH for two prepackages and 2.85 nH for four prepackages.
Horizontal chip cracks have been reported in various scientific publications on PCB embedded power semiconductor devices. This study investigates in detail the root cause of the cracks. Experimental evidence indicates that the chip fractures in the mechanical grinding process during preparation of the cross-sections. Here, two different factors are relevant: First, the mechanical fracture strength of the semiconductor die decreases when grinding its edge. The use of P320 sand paper reduces the characteristic fracture strength from 719 MPa to 211 MPa. Second, the tensile stresses in the chip edge increase considerably when, part of the die and package is removed by grinding. Both effects together result in a failure probability of 100%. The use of finer grain sandpaper for target preparation helps to reduce the probability of generating horizontal chip cracks during cross-sectioning.
Die Veröffentlichung beleuchtet die Herausforderungen und Lösungsansätze zur Bekämpfung des Fachkräftemangels innerhalb der produzierenden Industrie am Standort Deutschland. Der Mangel an qualifizierten Arbeitskräften führt zu erheblichen Kosten und reduziert das Produktionspotenzial. Hauptursachen sind der demographische Wandel und veränderte Wertvorstellungen der Beschäftigten. Es gillt, das Arbeitsumfeld Produktion attraktiver zu gestalten, indem individuelle Beiträge sichtbarer gemacht und das Gemeinschaftsgefühl gestärkt werden. Zudem soll die wahrgenommene Komplexität reduziert und die Autonomie des Fertigungspersonals erhöht werden. Beispiele wie ein digitales Ampelsystem und die Visualisierung individueller Beiträge verdeutlichen diese Ansätze. Die Zukunft der Produktion wird durch sieben Thesen skizziert, die die Bedeutung einer partizipativen Planung, die Veränderung der Anforderungen und die Notwendigkeit eines Kommunikationsraums betonen. Die Präsentation endet mit der Vision einer modernen, vollvernetzten und arbeitnehmerfreundlichen Produktionsstätte.
Many cities in Europe and around the world are concerned with reducing their CO2-emissions. One step on this agenda is the introduction of electric buses to replace combustion engines. The electrification of urban buses requires an accurate prediction of the energy demand. In this pa per, an energy model and the underlying calibration process is presented. This approach leverages substantial tracking data from 10 electric buses operated in Göttingen, Germany. It was shown that, with the use of additional information from the directly measured tracking data, like auxiliary power, charging power and vehicle weight, it is possible to precisely calibrate models based on physical equations with regard to generally poorly identifiable parameters like rolling friction coefficient or efficiency of the electric machine. With a multilayered approach for simulating the energy demand, it is possible to validate the results on the mechanical layer and on the electrical layer separately. This enables a far better parametrization and elimination of uncertainties from the different parameters. Furthermore, we compare the results to other publications for sections with 1 km, 100 km and 230 km, respectively. The relative errors between the simulated and measured electrical power consumption are below 0.3%, 3% and 6.5%, respectively. Hence, the yielded model is appropriate for electric urban bus network planning applications. And the found parameters should be a good starting point for other energy prediction models. To further enable comparability with other approaches the dataset used for calibration is made publicly available.
Many cities in Europe and around the world are concerned with reducing their CO2-emissions. One step on this agenda is the introduction of electric buses to replace combustion engines. The electrification of urban buses requires an accurate prediction of the energy demand. In this pa per, an energy model and the underlying calibration process is presented. This approach leverages substantial tracking data from 10 electric buses operated in Göttingen, Germany. It was shown that, with the use of additional information from the directly measured tracking data, like auxiliary power, charging power and vehicle weight, it is possible to precisely calibrate models based on physical equations with regard to generally poorly identifiable parameters like rolling friction coefficient or efficiency of the electric machine. With a multilayered approach for simulating the energy demand, it is possible to validate the results on the mechanical layer and on the electrical layer separately. This enables a far better parametrization and elimination of uncertainties from the different parameters. Furthermore, we compare the results to other publications for sections with 1 km, 100 km and 230 km, respectively. The relative errors between the simulated and measured electrical power consumption are below 0.3%, 3% and 6.5%, respectively. Hence, the yielded model is appropriate for electric urban bus network planning applications. And the found parameters should be a good starting point for other energy prediction models. To further enable comparability with other approaches the dataset used for calibration is made publicly available.
Produkte werden heutzutage immer variantenreicher und individueller. Für die industrielle Fertigung wachsen die Anforderungen, die Produkte effizient zu fertigen und schnell auf sich verändernde Marktbedingungen zu reagieren. Entsprechend rapide steigt die Nachfrage nach flexiblen Produktionslösungen, die sich möglichst autonom an die neuesten Marktanforderungen anpassen. Wandlungsfähige und modulare Produktionssysteme sollen es ermöglichen, auch bei großer Variantenvielfalt effizient zu produzieren - sogar bis zur Losgröße 1. Unterstützt wird die Produktion durch digitale Lösungen, die bereits an vielen Stellen zum Einsatz kommen.
Der Arbeits- und Fachkräftemangel wird seitens der produzierenden Industrie im DACH-Raum als zunehmend wachstumshemmend und geschäftsmodellbedrohend empfunden. Als zentrale Ursachen können gleichermaßen der demographische Wandel wie auch ein entsprechender Wertewandel ausgemacht werden. Es erscheint daher empfehlenswert, die "Ressource Mensch" in dieser Gemengelage neu zu denken. Die Frage, wie ein modernes Produktionssystem beschaffen sein muss, damit dieses aus Arbeitnehmersicht langfristig als attraktiv wahrgenommen wird, rückt hierbei in den Mittelpunkt wissenschaftlicher Überlegungen.
„Hybride Montage“ als Antwort auf Modell Mix und Variantenvielfalt im produzierenden Mittelstand
(2024)
Die "Hybride Montage" als Kombination aus konventioneller Fließfertigung und innovativer Matrixproduktion offeriert vielfältige Potentiale, dem zunehmenden Maß an Variantenvielfalt in der produzierenden Industrie Rechnung zu tragen. Im Zeitalter des Industrial Metsverse und der damit verbundenen "Servitisierung" und des "Manufacturing as a Service" - d.h. der Güterproduktion als Dienstleistung - ermöglicht die Hybride Montage außerdem eine flexiblere Arbeitsplanung.