TY - CHAP A1 - Adenacker, J. A1 - Gerhards, Benjamin A1 - Otten, Christian A1 - Schleser, Markus T1 - Laserstrahlschweißen von Aluminium-Kupfer-Werkstoffkombinationen für die Elektromobilität T2 - DVS CONGRESS 2021 Y1 - 2021 SN - 978-3-96144-146-4 N1 - DVS CONGRESS 2021, 14. – 17. September 2021, Essen. Große Schweißtechnische Tagung 2021, DVS CAMPUS 2021. DVS Berichte, Band: 371 SP - 31 EP - 38 PB - DVS Media GmbH CY - Düsseldorf ER - TY - JOUR A1 - Zabirov, Alexander A1 - Schleser, Markus A1 - Bucherer, Sebastian T1 - Füge- und Dichtkonzept für einen Leichtbauverbrennungsmotor JF - adhäsion KLEBEN & DICHTEN Y1 - 2021 U6 - https://doi.org/10.1007/s35145-021-0531-5 SN - 2192-8681 VL - 65 IS - 11 SP - 12 EP - 19 PB - Springer Nature CY - Cham ER - TY - JOUR A1 - Kasch, Susanne A1 - Schmidt, Thomas A1 - Jahn, Simon A1 - Eichler, Fabian A1 - Thurn, Laura A1 - Bremen, Sebastian T1 - Lösungsansätze und Verfahrenskonzepte zum Laserstrahlschmelzen von Glas JF - Schweissen und Schneiden Y1 - 2021 SN - 0036-7184 VL - 73 IS - Heft 1-2 SP - 32 EP - 39 PB - DVS Verlag CY - Düsseldorf ER - TY - CHAP A1 - Pfeiffer, Johann A1 - Balc, Nicolae A1 - Gebhardt, Andreas T1 - Studie zur Untersuchung der Auswirkung von Fräsbahnstrategien auf die Oberflächenqualität von mittels SLM gefertigten Metallteilen T2 - Tagungsband 21. Nachwuchswissenschaftler*innenkonferenz N2 - Für die Herstellung von metallischen Bauteilen wird in der heutigen Zeit eine Vielzahl von Verfahren auf dem Markt angeboten. Dabei stehen die additiven im Wettbewerb zu den konventionellen Verfahren. Die erreichbaren Oberflächenqualitäten der additiven sind nicht mit denen spanender Verfahren vergleichbar. Für diesen Beitrag wurde analysiert, ob sich ein mittels Selektivem Laserschmelzen (SLM) additiv hergestellter Edelstahl hinsichtlich seiner Oberflächenqualität nach der Zerspanung von einem umgeformten konventionell hergestellten Edelstahl gleicher Sorte unterscheidet. Y1 - 2021 SN - 978-3-932886-36-2 N1 - 21. Nachwuchswissenschaftler*innenkonferenz, Ernst-Abbe-Hochschule Jena, 26. und 27. Mai 2021 SP - 99 EP - 102 PB - Verlag Ernst-Abbe-Hochschule Jena CY - Jena ER - TY - CHAP A1 - Ulmer, Jessica A1 - Braun, Sebastian A1 - Cheng, Chi-Tsun A1 - Dowey, Steve A1 - Wollert, Jörg F. T1 - Adapting augmented reality systems to the users’ needs using gamification and error solving methods T2 - Procedia CIRP - 54th CIRP CMS 2021 - Towards Digitalized Manufacturing 4.0 N2 - Animations of virtual items in AR support systems are typically predefined and lack interactions with dynamic physical environments. AR applications rarely consider users’ preferences and do not provide customized spontaneous support under unknown situations. This research focuses on developing adaptive, error-tolerant AR systems based on directed acyclic graphs and error resolving strategies. Using this approach, users will have more freedom of choice during AR supported work, which leads to more efficient workflows. Error correction methods based on CAD models and predefined process data create individual support possibilities. The framework is implemented in the Industry 4.0 model factory at FH Aachen. KW - Augmented Reality KW - Adaptive Systems KW - Gamification KW - Error Recovery Y1 - 2021 U6 - https://doi.org/10.1016/j.procir.2021.11.024 SN - 2212-8271 N1 - CIRP CMS 2021 - 54th CIRP Conference on Manufacturing Systems, September 22-24, 2021, online VL - 104 SP - 140 EP - 145 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Braun, Sebastian A1 - Cheng, Chi-Tsun A1 - Dowey, Steve A1 - Wollert, Jörg F. T1 - Performance evaluation of skill-based order-assignment in production environments with multi-agent systems JF - IEEE Journal of Emerging and Selected Topics in Industrial Electronics N2 - The fourth industrial revolution introduces disruptive technologies to production environments. One of these technologies are multi-agent systems (MASs), where agents virtualize machines. However, the agent's actual performances in production environments can hardly be estimated as most research has been focusing on isolated projects and specific scenarios. We address this gap by implementing a highly connected and configurable reference model with quantifiable key performance indicators (KPIs) for production scheduling and routing in single-piece workflows. Furthermore, we propose an algorithm to optimize the search of extrema in highly connected distributed systems. The benefits, limits, and drawbacks of MASs and their performances are evaluated extensively by event-based simulations against the introduced model, which acts as a benchmark. Even though the performance of the proposed MAS is, on average, slightly lower than the reference system, the increased flexibility allows it to find new solutions and deliver improved factory-planning outcomes. Our MAS shows an emerging behavior by using flexible production techniques to correct errors and compensate for bottlenecks. This increased flexibility offers substantial improvement potential. The general model in this paper allows the transfer of the results to estimate real systems or other models. KW - cyber-physical production systems KW - event-based simulation KW - multi-agent systems KW - digital factory KW - industrial agents Y1 - 2021 U6 - https://doi.org/10.1109/JESTIE.2021.3108524 SN - 2687-9735 IS - Early Access PB - IEEE CY - New York ER - TY - CHAP A1 - Ulmer, Jessica A1 - Braun, Sebastian A1 - Wollert, Jörg F. T1 - Adaptive VR-Produktionsumgebungen für Evaluations- und Schulungstätigkeiten T1 - Adaptive VR production environments for evaluation and training purposes T2 - Automation 2021: Navigating towards resilient Production N2 - Industrie 4.0 stellt viele Herausforderungen an produzierende Unternehmen und ihre Beschäf-tigten. Innovative und effektive Trainingsstrategien sind erforderlich, um mit den sich schnell verändernden Produktionsumgebungen und neuen Fertigungstechnologien Schritt halten zu können. Virtual Reality (VR) bietet neue Möglichkeiten für On-the-Job, On-Demand- und Off-Premise-Schulungen. Diese Arbeit stellt ein neues VR Schulungssystem vor, welches sich flexible an unterschiedliche Trainingsobjekte auf Grundlage von Rezepten und CAD Modellen anpassen lässt. Das Konzept basiert auf gerichteten azyklischen Graphen und einem Level-system. Es ermöglicht eine benutzerindividuelle Lerngeschwindigkeit mittels visueller Ele-mente. Das Konzept wurde für einen mechanischen Anwendungsfall mit Industriekomponen-ten implementiert und in der Industrie 4.0-Modellfabrik der FH Aachen umgesetzt. N2 - Industry 4.0 poses many challenges for manufacturing companies and their employees. Inno-vative and effective training strategies are needed to keep pace with rapidly changing produc-tion environments and new manufacturing technologies. Virtual reality (VR) offers new oppor-tunities for on-the-job, on-demand, and off-premise training. This work presents a new VR training system that can be flexibly adapted to different training objects based on recipes and CAD models. The concept is based on directed acyclic graphs and a level system. It allows a user-individual learning speed by means of visual elements. The concept was implemented for a mechanical use case with industrial components and implemented in the industry 4.0 model factory of the FH Aachen University of Applied Sciences. Y1 - 2021 SN - 978-3-18-092392-5 U6 - https://doi.org/10.51202/9783181023921-55 SN - 0083-5560 N1 - 22. Leitkongress der Mess- und Automatisierungstechnik AUTOMATION 2021 - Navigating towards resilient Production, 29. und 30. Juni 2021 SP - 55 EP - 64 PB - VDI CY - Düsseldorf ER - TY - JOUR A1 - Abbas, Karim A1 - Balc, Nicolae A1 - Bremen, Sebastian A1 - Skupin, Marco T1 - Crystallization and aging behavior of polyetheretherketone PEEK within rapid tooling and rubber molding JF - Journal of Manufacturing and Materials Processing N2 - In times of short product life cycles, additive manufacturing and rapid tooling are important methods to make tool development and manufacturing more efficient. High-performance polymers are the key to mold production for prototypes and small series. However, the high temperatures during vulcanization injection molding cause thermal aging and can impair service life. The extent to which the thermal stress over the entire process chain stresses the material and whether it leads to irreversible material aging is evaluated. To this end, a mold made of PEEK is fabricated using fused filament fabrication and examined for its potential application. The mold is heated to 200 ◦C, filled with rubber, and cured. A differential scanning calorimetry analysis of each process step illustrates the crystallization behavior and first indicates the material resistance. It shows distinct cold crystallization regions at a build chamber temperature of 90 ◦C. At an ambient temperature above Tg, crystallization of 30% is achieved, and cold crystallization no longer occurs. Additional tensile tests show a decrease in tensile strength after ten days of thermal aging. The steady decrease in recrystallization temperature indicates degradation of the additives. However, the tensile tests reveal steady embrittlement of the material due to increasing crosslinking. KW - additive manufacturing KW - fused filament fabrication KW - crystallization KW - polyetheretherketone KW - rapid tooling Y1 - 2022 U6 - https://doi.org/10.3390/jmmp6050093 SN - 2504-4494 N1 - The article belongs to the Special Issue Advances in Injection Molding: Process, Materials and Applications VL - 6 IS - 5 SP - 1 EP - 12 PB - MDPI CY - Basel ER - TY - CHAP A1 - Dannen, Tammo A1 - Schindele, Benedikt A1 - Prümmer, Marcel A1 - Arntz, Kristian A1 - Bergs, Thomas T1 - Methodology for the self-optimizing determination of additive manufacturing process eligibility and optimization potentials in toolmaking T2 - Procedia CIRP Leading manufacturing systems transformation – Proceedings of the 55th CIRP Conference on Manufacturing Systems 2022 N2 - Additive Manufacturing (AM) of metallic workpieces faces a continuously rising technological relevance and market size. Producing complex or highly strained unique workpieces is a significant field of application, making AM highly relevant for tool components. Its successful economic application requires systematic workpiece based decisions and optimizations. Considering geometric and technological requirements as well as the necessary post-processing makes deciding effortful and requires in-depth knowledge. As design is usually adjusted to established manufacturing, associated technological and strategic potentials are often neglected. To embed AM in a future proof industrial environment, software-based self-learning tools are necessary. Integrated into production planning, they enable companies to unlock the potentials of AM efficiently. This paper presents an appropriate methodology for the analysis of process-specific AM-eligibility and optimization potential, added up by concrete optimization proposals. For an integrated workpiece characterization, proven methods are enlarged by tooling-specific figures. The first stage of the approach specifies the model’s initialization. A learning set of tooling components is described using the developed key figure system. Based on this, a set of applicable rules for workpiece-specific result determination is generated through clustering and expert evaluation. Within the following application stage, strategic orientation is quantified and workpieces of interest are described using the developed key figures. Subsequently, the retrieved information is used for automatically generating specific recommendations relying on the generated ruleset of stage one. Finally, actual experiences regarding the recommendations are gathered within stage three. Statistic learning transfers those to the generated ruleset leading to a continuously deepening knowledge base. This process enables a steady improvement in output quality. KW - Additive manufacturing KW - Laser-Powder Bed Fusion KW - L-PBF KW - Binder Jetting KW - Directed Energy Deposition Y1 - 2022 U6 - https://doi.org/10.1016/j.procir.2022.05.188 SN - 2212-8271 N1 - 55th CIRP Conference on Manufacturing Systems, Jun 29, 2022 - Jul 01, 2022, Lugano, Switzerland VL - 107 SP - 1539 EP - 1544 PB - Elsevier CY - Amsterdam ER - TY - CHAP A1 - Weiss, Christian A1 - Heslenfeld, Jonas A1 - Saewe, Jasmin Kathrin A1 - Bremen, Sebastian A1 - Häfner, Constantin Leon T1 - Investigation on the influence of powder humidity in Laser Powder Bed Fusion (LPBF) T2 - Procedia CIRP 12th CIRP Conference on Photonic Technologies [LANE 2022] N2 - In the Laser Powder Bed Fusion (LPBF) process, parts are built out of metal powder material by exposure of a laser beam. During handling operations of the powder material, several influencing factors can affect the properties of the powder material and therefore directly influence the processability during manufacturing. Contamination by moisture due to handling operations is one of the most critical aspects of powder quality. In order to investigate the influences of powder humidity on LPBF processing, four materials (AlSi10Mg, Ti6Al4V, 316L and IN718) are chosen for this study. The powder material is artificially humidified, subsequently characterized, manufactured into cubic samples in a miniaturized process chamber and analyzed for their relative density. The results indicate that the processability and reproducibility of parts made of AlSi10Mg and Ti6Al4V are susceptible to humidity, while IN718 and 316L are barely influenced. KW - LPBF KW - Additive Manufacturing KW - Powder Material KW - Humidity Y1 - 2022 U6 - https://doi.org/10.1016/j.procir.2022.08.102 SN - 2212-8271 N1 - 12th CIRP Conference on Photonic Technologies [LANE 2022], 04. September 2022 bis 08. September 2022, Fürth VL - 111 SP - 115 EP - 120 PB - Elsevier CY - Amsterdam ER -