https://opendata.uni-halle.de//handle/541532/27278 Fri, 10 Apr 2026 13:28:17 GMT 2026-04-10T13:28:17Z https://opendata.uni-halle.de//handle/1981185920/123887 Title: Entwicklung und praktische Anwendung eines hybriden Umlagerungsmodells in der Prototypenteilelogistik der Automobilindustrie Author(s): Vorwerk, Bastian Abstract: In logistics, transshipment models can lead to a significant reduction in transport costs and to realization of time advantages. A large number of reactive and proactive stock transfer models have already been presented in literature. Hybrid transshipment models, which combine reactive and proactive transshipments, have been researched less in literature. The special characteristic of prototype parts logistics is a batch size = 1, which means that each part can only be stored in one warehouse and cannot be replenished from the upstream echelon. As the few existing models proactively balance the stock > 1 of a part across several warehouse locations, they cannot be adapted to the special characteristic of prototype parts logistics in the automotive industry. Due to short-term demands of various assembly sites for the assembly of prototype vehicles and the need for a fast delivery, transportations to assembly sites and between warehouses are planned on a daily basis. The objective of the present work is to develop a new transshipment model specifically for unique parts and to validate it in practice. The aim is to store unique items in the best possible warehouse so that the right part can be delivered at the right time, to the right place and at the right costs. In the newly developed transshipment model, demand probabilities are determined for each part and each assembly location, which are used to calculate approximated future shipping costs as an indicator of the expected best warehouse. By combining a weighted and lexicographic target function, in which, for example, the minimization of the approximated future shipping costs is included, remaining vehicle capacities are used in the hybrid approach to implement proactive transshipments. The influence of various characteristics in the logistics network on the hybrid transshipment approach is investigated in a numerical study. For the model validation, the transshipment model is adapted to a practical application in the prototype parts logistics of Volkswagen AG and a case study is carried out. A machine learning model is trained and applied to forecast demand probabilities in the case study. In addition, a rule-based heuristic algorithm is developed to implement the hybrid approach in practice. The decision rules are integrated into a decision support system that generates a recommendation for the logistics planners on which parts to transship. The case study does not only show that the hybrid approach saves transportation costs, but also that the delivery time for customers can be significantly reduced. The model is formulated in such a way that it can be adapted to different use cases with unique items and demand probabilities. Thu, 01 Jan 2026 00:00:00 GMT https://opendata.uni-halle.de//handle/1981185920/123887 2026-01-01T00:00:00Z https://opendata.uni-halle.de//handle/1981185920/122687 Title: Encapsulation Polymer Degradation and Its Impact on the Deterioration of Solar Modules Author(s): Heidrich, Robert Abstract: This thesis deals with the basic degradation mechanisms of solar modules, focusing on the polymer encapsulation materials used and the additives they contain. Using self-developed measurement methods based on pyrolysis gas chromatography mass spectrometry (PY-GCMS) and ultraviolet-visible (UV/VIS) spectrophotometry, the quantification of these additives is carried out, enabling a variety of further analysis approaches. On the one hand, fundamental effects such as additive diffusion are studied within this work. On the other hand, the degradation behavior of the polymers is investigated as a function of the stabilizing additives. In this work, solar modules are subjected to different stress conditions such as UV irradiation, high humidity, and high temperatures as part of accelerated aging tests. The stressors are used individually and in combination to analyze the resulting degradation effects of the solar modules. The analyses include macroscopic characterization methods such as I-V and electroluminescence (EL) measurements as well as various methods of polymer analysis such as Fourier transform infrared spectrometry (FTIR), evolved gas analysis (EGA)-FTIR, differential scanning calorimetry (DSC) and UV/VIS spectrophotometry. The interactions of the additives were determined using PY-GCMS, electron paramagnetic resonance spectroscopy (EPR), and Orbitrap mass spectrometry. By combining these measurement methods, it was possible to trace the degradation chain of solar modules from the consumption of stabilizing additives through the degradation of the encapsulation polymers to the degradation of the solar cell itself and its electrical connectors. In particular, the degradation reactions to be expected due to the prevailing microclimate at different positions within the modules could be investigated. In this context, models that predict the degradation of UV stabilizers and UV absorbers could be derived depending on the environmental parameters. The UV aging standard IEC 62788-7-2 was also validated thanks to the large number of accelerated aging series carried out. It was found that the UV-A fluorescent lamps listed in the standard, in contrast to xenon lamps with daylight filters, do not lead to the aging effects observed in the field. Consequently, the former are to be classified as unsuitable for qualifying polymer materials for solar modules. On the one hand, various fundamental effects, such as additive interactions in multi- layer systems and their diffusion behavior, can be derived from the results of the work. On the other hand, clear conclusions can be drawn for the industry to increase the service life of solar modules in the future. The latter is of particular interest for the introduction of new cell technologies such as TOPCon (tunnel oxide passivated contact) or HJT (hetero junction) and the associated new encapsulation materials POE (polyolefin elastomer) and TPO (thermoplastic polyolefin). Wed, 01 Jan 2025 00:00:00 GMT https://opendata.uni-halle.de//handle/1981185920/122687 2025-01-01T00:00:00Z https://opendata.uni-halle.de//handle/1981185920/116927 Title: Methods and algorithms for detecting and classifying moving objects based on the evaluation of an object’s geometrical parameters in an image sequence for smart lighting systems Author(s): Matveev, Ivan Abstract: Modern machine learning based object detection methods have high accuracy; however, at the same time, they require the increased computing power of processing units. Thus, widespread low-performance IoT devices generating a substantial amount of data cannot apply corresponding machine learning algorithms for real-time data processing due to a lack of local computational resources. The Dimensional Based Object Detection (DBOD) algorithm for low-performance single-board computers is developed and evaluated in the course of this dissertation. The proposed algorithm exploits geometrical features of objects in an image and real-world scene parameters (e.g. camera’s focal length, height and angle of installation) as classification features. Extraction and classification of these features are computationally simple procedures that single-board computers can execute in real-time. The algorithm is focused on detecting and classifying objects that are the most expected in urban environments: pedestrians, bicyclists, and vehicles. The algorithm can be applied for processing video sequences captured by a CCTV camera. A method for fast generating synthetic training features for the DBOD has been proposed. The algorithm DBOD has been tested on real and synthetically generated datasets. The results have shown that low-performance systems, such as popular Raspberry Pi, are capable of object classification with the required frame rate and accuracy for smart city applications. Mon, 01 Jan 2024 00:00:00 GMT https://opendata.uni-halle.de//handle/1981185920/116927 2024-01-01T00:00:00Z https://opendata.uni-halle.de//handle/1981185920/112829 Title: Analyse von Methoden zur Wärmeerzeugung in Einfamilienhäusern mit Strom aus Photovoltaik Author(s): Müller, Willy Thu, 27 Apr 2023 00:00:00 GMT https://opendata.uni-halle.de//handle/1981185920/112829 2023-04-27T00:00:00Z