Universität Stuttgart
Permanent URI for this communityhttps://elib.uni-stuttgart.de/handle/11682/1
Browse
81 results
Search Results
Item Open Access Scoping review of potentials to optimize planar solid oxide cell designs for use in fuel cell and electrolysis applications(2025) Malicek, Bernhard; Speckmann, Friedrich-Wilhelm; Entenmann, Marc; Birke, Kai PeterThis scoping review evaluates the literature on options for planar solid oxide cell (SOC) performance optimization, with a focus on applied fabrication methods and design enhancements. Literature identification, selection, and charting followed PRISMA-ScR guidelines to ensure transparency, reproducibility, and comprehensive coverage, while also enabling the identification of research gaps beyond the scope of narrative reviews. We analyze the influence of fabrication methods on cell and component characteristics and evaluate optimization approaches identified in the literature. Subsequent discussion explores how design innovations intersect with fabrication choices. The surveyed literature reveals a broad spectrum of manufacturing methods, including conventional processes, thin-film deposition, infiltration, and additive manufacturing. Our critical assessment of scalability revealed that reduction in operating temperature, improving robustness, and electrochemical performance are the main optimization objectives for SOC designs. Regarding production cost, production scale-up, and process control, inkjet, electrophoretic deposition, and solution aerosol thermolysis appeared to be promising manufacturing methods for design enhancements. By combining the PRISMA-ScR evidence map with a synthesis focused on scalability and process control, this review provides practical insights and a strong foundation for future SOC research and scale-up, also for evolving the field of proton-conducting cells.Item Open Access Enzyme-assisted circular additive manufacturing as an enabling technology for a circular bioeconomy : a conceptual review(2024) Protte-Freitag, Kristin; Gotzig, Sophia; Rothe, Hannah; Schwarz, Oliver; Silber, Nadine; Miehe, RobertAdditive manufacturing (AM) is a decisive element in the sustainable transformation of technologies. And yet its inherent potential has not been fully utilized. In particular, the use of biological materials represents a comparatively new dimension that is still in the early stages of deployment. In order to be considered sustainable and contribute to the circular economy, various challenges need to be overcome. Here, the literature focusing on sustainable, circular approaches is reviewed. It appears that existing processes are not yet capable of being used as circular economy technologies as they are neither able to process residual and waste materials, nor are the produced products easily biodegradable. Enzymatic approaches, however, appear promising. Based on this, a novel concept called enzyme-assisted circular additive manufacturing was developed. Various process combinations using enzymes along the process chain, starting with the preparation of side streams, through the functionalization of biopolymers to the actual printing process and post-processing, are outlined. Future aspects are discussed, stressing the necessity for AM processes to minimize or avoid the use of chemicals such as solvents or binding agents, the need to save energy through lower process temperatures and thereby reduce CO2 consumption, and the necessity for complete biodegradability of the materials used.Item Open Access Marker‐free traceability in battery production from continuous electrode foils to cell‐specific individual electrode segments(2025) Regina, David J.; Riexinger, Günther; Schmid‐Schirling, Tobias; Landwehr, Inga; Rödel, Lars; Sauer, Alexander; Carl, DanielThis article presents advancements in the Track & Trace Fingerprint technology applied to lithium‐ion battery production, focusing on its innovative approach to material identification using unique surface microstructures. Traditional traceability methods often compromise material integrity through physical markers or fail when continuous material (e.g., electrode or other web material) is interrupted. This technology eliminates these issues by leveraging marker‐free identification, enabling reliable tracking of continuous and segmented electrode materials without altering their properties. Experimental results demonstrate the effectiveness of the technology across various materials, including aluminum, copper, graphite, lithium‐iron‐phosphate, and nickel‐manganese‐cobalt coatings, with high identification rates and robust traceability. Additionally, software enhancements have improved predictive algorithms for estimating fingerprint locations, increasing processing speed and efficiency. Future developments will focus on graphics processing unit acceleration and optimized local database management to increase the current supported feed rate from 25 m min -1 to 60 m min -1 or more to broaden applicability. The technology's versatility extends beyond battery production, with potential applications in other continuous manufacturing processes, such as paper and steel production.Item Open Access A methodology to systematically identify and characterize energy flexibility measures in industrial systems(2020) Tristán, Alejandro; Heuberger, Flurina; Sauer, AlexanderIndustrial energy flexibility enables companies to optimize their energy-associated production costs and support the energy transition towards renewable energy sources. The first step towards achieving energy flexible operation in a production facility is to identify and characterize the energy flexibility measures available in the industrial systems that comprise it. These industrial systems are both the manufacturing systems that directly execute the production tasks and the systems performing supporting tasks or tasks necessary for the operation of these manufacturing systems. Energy flexibility measures are conscious and quantifiable actions to carry out a defined change of operative state in an industrial system. This work proposes a methodology to identify and characterize the available energy flexibility measures in industrial systems regardless of the task they perform in the facility. This methodology is the basis of energy flexibility-oriented industrial energy audits, in juxtaposition with the current industrial energy audits that focus on energy efficiency. This audit will provide industrial enterprises with a qualitative and quantitative understanding of the capabilities of their industrial systems, and hence their production facilities, for energy flexible operation. The audit results facilitate a company’s decision making towards the implementation, evaluation and management of these capabilities.Item Open Access Optimization of disassembly strategies for electric vehicle batteries(2021) Baazouzi, Sabri; Rist, Felix Paul; Weeber, Max; Birke, Kai PeterVarious studies show that electrification, integrated into a circular economy, is crucial to reach sustainable mobility solutions. In this context, the circular use of electric vehicle batteries (EVBs) is particularly relevant because of the resource intensity during manufacturing. After reaching the end-of-life phase, EVBs can be subjected to various circular economy strategies, all of which require the previous disassembly. Today, disassembly is carried out manually and represents a bottleneck process. At the same time, extremely high return volumes have been forecast for the next few years, and manual disassembly is associated with safety risks. That is why automated disassembly is identified as being a key enabler of highly efficient circularity. However, several challenges need to be addressed to ensure secure, economic, and ecological disassembly processes. One of these is ensuring that optimal disassembly strategies are determined, considering the uncertainties during disassembly. This paper introduces our design for an adaptive disassembly planner with an integrated disassembly strategy optimizer. Furthermore, we present our optimization method for obtaining optimal disassembly strategies as a combination of three decisions: (1) the optimal disassembly sequence, (2) the optimal disassembly depth, and (3) the optimal circular economy strategy at the component level. Finally, we apply the proposed method to derive optimal disassembly strategies for one selected battery system for two condition scenarios. The results show that the optimization of disassembly strategies must also be used as a tool in the design phase of battery systems to boost the disassembly automation and thus contribute to achieving profitable circular economy solutions for EVBs.Item Open Access Comparison of the temperature, radiation, and heat flux distribution of a hydrogen and a methane flame in a crucible furnace using numerical simulation(2024) Mages, Alexander; Sauer, AlexanderSustainable technologies to replace current fossil solutions are essential to meet future CO2 emission reduction targets. Therefore, this paper compares key performance indicators of a hydrogen- and a methane-flame-fired crucible furnace with computational fluid dynamics simulations at identical firing powers, aiming to fully decarbonize the process. Validated numerical models from the literature were used to compare temperatures, radiation fields, radiation parameters and heat transfer characteristics. As a result, we observed higher combustion temperatures and a 19.0% higher fuel utilization rate in the hydrogen case, indicating more efficient operating modes, which could be related to the increased radiant heat flux and temperature ranges above 1750 K. Furthermore, higher scattering of the heat flux distribution on the crucible surface could be determined indicating more uneven melt bath temperatures. Further research could focus on quantifying the total fuel consumption required for the heating up of the furnace, for which a transient numerical model could be developed.Item Open Access A reinforcement learning approach to view planning for automated inspection tasks(2021) Landgraf, Christian; Meese, Bernd; Pabst, Michael; Martius, Georg; Huber, Marco F.Manual inspection of workpieces in highly flexible production facilities with small lot sizes is costly and less reliable compared to automated inspection systems. Reinforcement Learning (RL) offers promising, intelligent solutions for robotic inspection and manufacturing tasks. This paper presents an RL-based approach to determine a high-quality set of sensor view poses for arbitrary workpieces based on their 3D computer-aided design (CAD). The framework extends available open-source libraries and provides an interface to the Robot Operating System (ROS) for deploying any supported robot and sensor. The integration into commonly used OpenAI Gym and Baselines leads to an expandable and comparable benchmark for RL algorithms. We give a comprehensive overview of related work in the field of view planning and RL. A comparison of different RL algorithms provides a proof of concept for the framework’s functionality in experimental scenarios. The obtained results exhibit a coverage ratio of up to 0.8 illustrating its potential impact and expandability. The project will be made publicly available along with this article.Item Open Access Multi-method model for the investigation of disassembly scenarios for electric vehicle batteries(2023) Baazouzi, Sabri; Grimm, Julian; Birke, Kai PeterDisassembly is a pivotal technology to enable the circularity of electric vehicle batteries through the application of circular economy strategies to extend the life cycle of battery components through solutions such as remanufacturng, repurposing, and efficient recycling, ultimately reintegrating gained materials into the production of new battery systems. This paper aims to develop a multi-method self-configuring simulation model to investigate disassembly scenarios, taking into account battery design as well as the configuration and layout of the disassembly station. We demonstrate the developed model in a case study using a Mercedes-Benz battery and the automated disassembly station of the DeMoBat project at Fraunhofer IPA. Furthermore, we introduce two disassembly scenarios: component-oriented and accessibility-oriented disassembly. These scenarios are compared using the simulation model to determine several indicators, including the frequency of tool change, the number and distribution of robot routes, tool utilization, and disassembly time.Item Open Access Model-based biomechanical exoskeleton concept optimization for a representative lifting task in logistics(2022) Schiebl, Jonas; Tröster, Mark; Idoudi, Wiem; Gneiting, Elena; Spies, Leon; Maufroy, Christophe; Schneider, Urs; Bauernhansl, ThomasOccupational exoskeletons are a promising solution to prevent work-related musculoskeletal disorders (WMSDs). However, there are no established systems that support heavy lifting to shoulder height. Thus, this work presents a model-based analysis of heavy lifting activities and subsequent exoskeleton concept optimization. Six motion sequences were captured in the laboratory for three subjects and analyzed in multibody simulations with respect to muscle activities (MAs) and joint forces (JFs). The most strenuous sequence was selected and utilized in further simulations of a human model connected to 32 exoskeleton concept variants. Six simulated concepts were compared concerning occurring JFs and MAs as well as interaction loads in the exoskeleton arm interfaces. Symmetric uplifting of a 21 kg box from hip to shoulder height was identified as the most strenuous motion sequence with highly loaded arms, shoulders, and back. Six concept variants reduced mean JFs (spine: >70%, glenohumeral joint: >69%) and MAs (back: >63%, shoulder: >59% in five concepts). Parasitic loads in the arm bracing varied strongly among variants. An exoskeleton design was identified that effectively supports heavy lifting, combining high musculoskeletal relief and low parasitic loads. The applied workflow can help developers in the optimization of exoskeletons.Item Open Access An exploratory analysis of the current status and potential of service-oriented and data-driven business models within the sheet metal working sector : insights from interview-based research in small and medium-sized enterprises(2024) Wirth, Jonas; Schneider, Mirko; Hanselmann, Leon; Fink, Kira; Nebauer, Stephan; Bauernhansl, ThomasResponding to changing value creation processes in the sheet metal working sector, where the complexity and interchangeability of products challenge traditional differentiation strategies, this exploratory analysis examines the integration of service-oriented and data-driven business models as new paths to ensure competitiveness, especially for small and medium-sized enterprises (SMEs). This study aims to capture the current state and challenges associated with the implementation of these business models in this sector. This research was conducted through semi-structured interviews with SMEs in the industry. The findings indicate that service-oriented and data-driven business models are not yet widely adopted and that manufacturing companies require support in their implementation. Fields of action were identified for the industry. These are “Creating awareness and understanding”, “Recognizing added value”, “Increasing company maturity”, and “Understanding the change process”. Cooperation between science and industry is essential in tackling these fields of action to ensure the successful integration of such business models in manufacturing companies. This paper identifies challenges in the fields of action that companies must address through a structured approach, promoting awareness, recognizing value, improving organizational maturity, and understanding the change process to successfully implement service-oriented and data-driven business models.