Raza, Syed Muhammad
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Publication Access status: Open Access , Datengestützte Umformtechnik: Künstliche Intelligenz zwischen Prozesswissen, Regelung und ProduktionsrealitätWith the 7th Biegeforum, the Chair of Forming Technology at the University of Siegen once again offers researchers the opportunity to present their topics and findings to a specialist audience from industry and academia. This conference volume brings together current research findings and innovative developments in forming technology, highlighting the broad scope of the research field. The Biegeforum thus underscores its role as a key platform for exchange between research and industry — a role it has fulfilled since its first edition in 2011.Source Type:Conference ProceedingsSeries:Forschungsberichte des Lehrstuhls für Umformtechnik1 30 - Some of the metrics are blocked by yourconsent settings
Publication Access status: Metadata only , Embedding optical fiber with laser metal depositionIn contrast to other additive manufacturing technologies, laser metal deposition (LMD) allows printing on existing metal parts. For smart tools, it would be advantageous to place fiber optics closely beneath surfaces in order to measure parameters, such as temperature and strains. This work presents a novel method to weld in fiber optical cables beneath sheet metal surfaces with LMD. Results show that the fiber optical cable can be enclosed in the metal, confirming the possibility of using LMD to embed fiber optical sensors in the metals. An applicable scan speed for welding has been identified. A need for a metallic strip on the surface of fiber has been identified, which prevents the fiber from being melted. Ceramic sleeve and multiple plastic layers around the cable successfully prevent the fiber from being destroyed. Further research on effects on the optical characteristics of the fibers is proposed.Source Type:Article3 - Some of the metrics are blocked by yourconsent settings
Publication Human Assistance System Supporting Forming Machine ReconfigurationIncreased product complexity in present manufacturing sector, shorter product lifecycles, and more variable customer demands, require production systems to be flexible and reliable. As a result, machines are required to be reconfigured more frequently and within shorter timeframes. Reconfiguring forming machines is a complex and delicate task that depends strongly on operator experience and practical know-how gained over several years. Appropriate support system is required to transfer the accumulated experience and knowledge in order to enable novice operators to perform such tasks effectively. This work presents an assistance system designed to support novice operators during forming machine reconfiguration tasks. The proposed system comprises an eye-gaze sensor to observe operator actions and visual attention during task execution. Based on this information, the system identifies potential mistakes and provides real-time feedback on a smartwatch to guide the operator through the reconfiguration process. The approach is evaluated in a controlled laboratory environment, where both task performance and user experience are assessed. The results show potential for the use of human assistance systems to support novice operators in real time during forming machine reconfiguration on the shop floor. In addition to improving the overall system and its evaluation in a real production environment under industrial conditions, future work will focus on multimodal sensor fusion to enable more robust intent recognition and contextual understanding of an operator during reconfiguration of forming machines.Source Type:InProceedings