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Keywords
Industry 4.0 imposes many challenges for manufacturing companies and their employees. Innovative and effective training strategies are required to cope with fast-changing production environments and new manufacturing technologies. Virtual Reality (VR) offers new ways of on-the-job, on-demand, and off-premise training. A novel concept and evaluation system combining Gamification and VR practice for flexible assembly tasks is proposed in this paper and compared to existing works. It is based on directed acyclic graphs and a leveling system. The concept enables a learning speed which is adjustable to the users’ pace and dynamics, while the evaluation system facilitates adaptive work sequences and allows employee-specific task fulfillment. The concept was implemented and analyzed in the Industry 4.0 model factory at FH Aachen for mechanical assembly jobs.
Generating synthetic LiDAR point cloud data for object detection using the Unreal Game Engine
(2024)
Object detection based on artificial intelligence is ubiquitous in today’s computer vision research and application. The training of the neural networks for object detection requires large and high-quality datasets. Besides datasets based on image data, datasets derived from point clouds offer several advantages. However, training datasets are sparse and their generation requires a lot of effort, especially in industrial domains. A solution to this issue offers the generation of synthetic point cloud data. Based on the design science research method, the work at hand proposes an approach and its instantiation for generating synthetic point cloud data based on the Unreal Engine. The point cloud quality is evaluated by comparing the synthetic cloud to a real-world point cloud. Within a practical example the applicability of the Unreal Game engine for synthetic point cloud generation could be successfully demonstrated.
Geräuschminderung und Leichtbau in Leistungsgetrieben durch den Einsatz von Werkstoffverbunden
(2007)
Durch die Fragmentierung von Wertschöpfungsketten ergeben sich neue Herausforderungen für das Management von Kundenbeziehungen. Die Dissertation untersucht die daraus resultierenden Anforderungen an eine übergreifende Integration von Customer Relationship Management in der
Telekommunikationsindustrie. Ziel ist es, durch Anwendung von Methoden eines Enterprise Architecture Framework eine übergreifend Lösung zu gestalten. Grundlegende Prämisse dabei ist, dass die übergreifende Gestaltung eines Customer Relationship Management für alle an der
Wertschöpfung beteiligten Unternehmen vorteilhaft ist.