Technische Universität Dresden: Qucosa
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Hybrid Simulation for Energy-Oriented Production Scheduling: Linking Material Flow Simulation and Constraint Programming for a Semiconductor Front-end Use Case
The concept of energy-oriented production scheduling has been receiving increased interest within the last decade. Despite its maturity in theoretical discourse, the adoption in practical settings is still at a preliminary stage. One reason for this may lie in the uncertainty of decision makers regarding the impact of energy-oriented production planning on shopfloor performance. In this manner, material flow simulation serves as a suitable instrument for evaluating energyoriented scheduling in silico. This article presents a hybrid simulation approach, embedding a Constraint Programming based scheduling model within a discrete event simulation model. Based on a real-world use case, our study analyses improvement potential of energy-oriented production scheduling for a semiconductor front-end area. Simulation results indicate that energy costs and peak demand can be reduced notably compared to traditional production control
Potenziale von Large Language Models zur Unterstützung der Modellierung von Simulationseingabedaten
The simulation of complex systems, for example in production and logistics, is essential for the planning and control of such systems. A key aspect of this is the modeling of input data, as the quality of the results depends heavily on the accuracy of this data. However, conventional methods are often complex, error-prone and require in-depth specialist knowledge. Large language models (LLMs) offer new potential for automation, as they are able to analyze complex data and process it in natural language. This article examines if and to what extent LLMs can improve and support the process of simulation input data modeling
Auf dem Weg zu nachhaltiger Reverse Logistics: Twin Transition mit Hilfe von Simulation in Closed- Loop Supply Chains
This paper presents a simulation-based approach to support the twin transition in reverse logistics within closed-loop supply chains (CLSCs). Using the example of the return of empties in the brewing industry, a discrete-event simulation (DES) model is developed to address complexity, uncertainty, and data gaps along the supply chain. The simulation integrates real data and domain knowledge to evaluate return scenarios, bottlenecks within logistics, and sustainability strategies. The use case highlights the lack of transparency, especially in consumer return behavior and intermediate distribution stages. The results underline the potential of DES in developing digital supply chain twins for decision support in sustainable logistics. Future work includes sensitivity analyses, scenario testing, and the integration of seasonal and regional behavior patterns for improved forecasting and strategic planning
Bewertung der Genauigkeit verschiedener Ansätze zur Formzahlberechnung
Aufgrund der hohen Anforderungen an Funktion und Kompaktheit sind Wellen und Achsen geometrisch meist sehr komplex. Zur Erfüllung vieler Bauteilfunktionen sind Kerben, wie z.B. ein Wellenabsatz oder eine Sicherungsringnut, notwendig. Diese führen jedoch zu einer erhöhten Bauteilbeanspruchung und stellen somit kritische Stellen für ein Bauteilversagen dar. Für eine sichere Bauteilauslegung sind daher genaue Methoden zur Ermittlung der Spannungserhöhung an Kerbstellen unerlässlich.
Für die Berechnung der Formzahl gibt es verschiedene Ansätze. Diese sind jedoch bekanntermaßen mit erheblichen Unsicherheiten behaftet. Daher sind sie für anspruchsvolle Anwendungen möglicherweise nicht immer ausreichend genau. Aus diesem Grund wurden in verschiedenen Forschungsarbeiten neue Gleichungen für die Formzahlberechnung entwickelt.
Ziel dieser Bachelorarbeit ist es, die Ansätze hinsichtlich ihrer Genauigkeit und Anwendbarkeit im Auslegungsprozess zu vergleichen. Es sollen Vor- und Nachteile aufgezeigt und Empfehlungen für die praktische Anwendung zur Ermittlung der Spannungserhöhung an Kerbstellen von Wellen abgeleitet werden.:1. Einleitung
1.1. Aufbau
2. Stand der Technik
2.1. Lastfälle und Beanspruchungen
2.2. Kerbarten und Kerbwirkung
2.2.1. Kerbarten
2.2.2. Kerbwirkung
2.2.3. Formzahl
2.3. Analytische Methoden der Formzahlberechnung
2.3.1. Allgemeine Ausführungen
2.3.2. DIN 743-2 und FKM
2.3.3. Melzer
2.3.4. Mayr-18
2.3.5. Noda
2.4. Numerische Methoden der Formzahlbestimmung
2.4.1. Allgemeine Ausführungen
2.4.2. FEM-Programm KERBERT
2.5. Kriterien für Genauigkeitsuntersuchung
3. Vergleich der Anwendbarkeit
4. FEM Berechnungen
4.1. Konvergenzstudie
5. Untersuchung der Genauigkeit
5.1. Umlaufende Rundnut
5.1.1. Zugbelastung
5.1.2. Biegebelastung
5.1.3. Torsionsbelastung
5.2. Abgesetzte Welle
5.2.1. Zugbelastung
5.2.2. Biegebelastung
5.2.3. Torsionsbelastung
5.3. Fazit
6. Zusammenfassung
Abbildungsverzeichnis
Tabellenverzeichnis
Literaturverzeichni
Rezension: „Von der Mathematisierung in der Ökonomie zur modernen Finanzmathematik (Agnes Handwerk)“: Buchbesprechung - Book Review
In ihrem Buch „Von der Mathematisierung in der Ökonomie zur modernen Finanzmathematik“ zeichnet die Journalistin Agnes Handwerk die Entstehungsgeschichte der modernen Finanzmathematik nach. Ausgehend von der „Formalist Revolution“ der Wirtschaftswissenschaften in den 1950er-Jahren bis zur Finanzkrise 2007/08 wird diese Entwicklung vor allem aus dem Blickwinkel deutscher und europäischer Mathematiker und mathematisch ausgebildeter Ökonomen erzählt. Neben Archiv- und Literaturrecherche sind Interviews mit den Wissenschaftlern Freddy Delbaen, Paul Embrechts, Hans Föllmer, Werner Hildenbrand, Thomas Mikosch und Dieter Sondermann eine wesentliche Grundlage von Agnes Handwerks Buch. Ein geplantes Interview mit dem 2014 verstorbenen Mathematiker Marc Yor kam nicht mehr zustande [...aus dem Text
CraneFlow: An Open-Source Python Framework for Modelling Bridge and Gantry Cranes
This paper introduces CraneFlow, a novel simulation framework for bridge and gantry cranes. By combining salabim’s discrete-event simulation environment and ruckig for time-optimal trajectory planning with jerk limits, CraneFlow enables detailed, load-dependent motion modelling. The framework is fully open source, allowing for extensive customization and integrations. To assess the need for detailed crane motion modelling, we present a systematic evaluation of six major simulation platforms, analysing their support for axis-specific motion constraints (velocity, acceleration, deceleration, jerk), concurrency patterns, as well as scheduling and collision avoidance logic. In a real-world case study of an automated coil storage yard, we show that higher-fidelity motion representations can significantly alter throughput estimates and thus system design decisions
Shifts from cooperative to individual-based predation defense determine microbial predator-prey dynamics
Predation defense is an important feature of predator-prey interactions adding complexity to ecosystem dynamics. Prey organisms have developed various strategies to escape predation which differ in mode (elude vs. attack), reversibility (inducible vs. permanent), and scope (individual vs. cooperative defenses). While the mechanisms and controls of many singular defenses are well understood, important ecological and evolutionary facets impacting long-term predator-prey dynamics remain underexplored. This pertains especially to trade-offs and interactions between alternative defenses occurring in prey populations evolving under predation pressure. Here, we explored the dynamics of a microbial predator-prey system consisting of bacterivorous flagellates (Poteriospumella lacustris) feeding on Pseudomonas putida. Within five weeks of co-cultivation corresponding to about 35 predator generations, we observed a consistent succession of bacterial defenses in all replicates (n = 16). Initially, bacteria expressed a highly effective cooperative defense based on toxic metabolites, which brought predators close to extinction. This initial strategy, however, was consistently superseded by a second mechanism of predation defense emerging via de novo mutations. Combining experiments with mathematical modeling, we demonstrate how this succession of defenses is driven by the maximization of individual rather than population benefits, highlighting the role of rapid evolution in the breakdown of social cooperation
Trimethoprim resistance in surface and wastewater is mediated by contrasting variants of the dfrB gene
Trimethoprim (TMP) is a low-cost, widely prescribed antibiotic. Its effectiveness is increasingly challenged by the spread of genes coding for TMP-resistant dihydrofolate reductases: dfrA, and the lesser-known, evolutionarily unrelated dfrB. Despite recent reports of novel variants conferring high level TMP resistance (dfrB10 to dfrB21), the prevalence of dfrB is still unknown due to underreporting, heterogeneity of the analyzed genetic material in terms of isolation sources, and limited bioinformatic processing. In this study, we explored a coherent set of shotgun metagenomic sequences to quantitatively estimate the abundance of dfrB gene variants in aquatic environments. Specifically, we scanned sequences originating from influents and effluents of municipal sewage treatment plants as well as river-borne microbiomes. Our analyses reveal an increased prevalence of dfrB1, dfrB2, dfrB3, dfrB4, dfrB5, and dfrB7 in wastewater microbiomes as compared to freshwater. These gene variants were frequently found in genomic neighborship with other resistance genes, transposable elements, and integrons, indicating their mobility. By contrast, the relative abundances of the more recently discovered variants dfrB9, dfrB10, and dfrB13 were significantly higher in freshwater than in wastewater microbiomes. Moreover, their direct neighborship with other resistance genes or markers of mobile genetic elements was significantly less likely. Our findings suggest that natural freshwater communities form a major reservoir of the recently discovered dfrB gene variants. Their proliferation and mobilization in response to the exposure of freshwater communities to selective TMP concentrations may promote the prevalence of high-level TMP resistance and thus limit the future effectiveness of antimicrobial therapies
Utilization of delactosed whey permeate for the synthesis of ethyl acetate with Kluyveromyces marxianus
Ethyl acetate is an important organic solvent and currently produced from fossil carbon resources. Microbial synthesis of this ester from sugar-rich waste could be an interesting alternative. Therefore, synthesis of ethyl acetate by Kluyveromyces marxinanus DSM 5422 from delactosed whey permeate (DWP) was studied in an aerated stirred bioreactor at 40 °C. DWP is mainly composed of residual lactose and minerals. The minerals inhibited yeast growth, as witnessed by an increased lag period, a reduced growth rate, and an extended process duration. All experiments were therefore carried out with diluted DWP. In a series of batch experiments, the pH of iron-deficient DWP medium varied between 4.8 and 5.9. The pH of the cultivation medium significantly influenced cell growth and product syntheses, with the highest ethyl acetate yield of 0.347 g g–1 and lowest by-product formation achieved at pH 5.1. It is likely that this effect is due to pH-dependent iron chelation, which affects the iron bioavailability and the intracellular iron content, thus affecting growth and metabolite synthesis. The viability of yeast cells was always high despite the harsh conditions in DWP medium, which enabled extended usage of the biomass in repeated-batch and fed-batch cultivations. These two culture techniques increased the volume of DWP processed per time by 32 and 84% for the repeated-batch and the fed-batch cultivation, respectively, without a drop of the ester yield.
Key points:
- Delactosed whey permeate was converted to ethyl acetate with a high rate and yield.
-The formation of ethyl acetate in DWP medium at iron limitation is pH-dependent.
- Highly active yeasts from batch processes enabled extension as fed and repeated batc