TY - JOUR AU - Schöppner, Volker AU - Austermeier, Laura AU - Brüning, Florian AU - Oldemeier, Jan Philipp AU - Brandt, O. ID - 52833 IS - 8/2023 JF - EXTRUSION SN - 2190-4774 TI - Recycling-Ansatz für mehrkomponentige Kunststoffprodukte durch thermische Verbundtrennung ER - TY - CONF AU - Schöppner, Volker AU - Arndt, Theresa ID - 52840 T2 - 76th Annual Assembly of the International Institute of Welding (IIW) TI - Anvil-free ultrasonic welding for welding situations with one sided access ER - TY - JOUR AU - Brüning, Florian AU - Kleinschmidt, Dennis AU - Petzke, J. ID - 52836 IS - 03/2023 JF - Kunststoffland NRW Report TI - Elastomerrecycling mittels Mikrowellenstrahlung ER - TY - JOUR AU - Moritzer, Elmar AU - Kartelmeyer, S. AU - Kringe, R. AU - Jaroschek, C. ID - 52837 IS - 8/2023 JF - Plastics Insights TI - Conformal Cooling at Low Cost ER - TY - CONF AB - Manufacturing companies face the challenge of reaching required quality standards. Using optical sensors and deep learning might help. However, training deep learning algorithms require large amounts of visual training data. Using domain randomization to generate synthetic image data can alleviate this bottleneck. This paper presents the application of synthetic image training data for optical quality inspections using visual sensor technology. The results show synthetically generated training data are appropriate for visual quality inspections. AU - Gräßler, Iris AU - Hieb, Michael ID - 52816 KW - synthetic training data KW - machine vision quality gates KW - deep learning KW - automated inspection and quality control KW - production control T2 - Lectures TI - Creating Synthetic Training Datasets for Inspection in Machine Vision Quality Gates in Manufacturing ER - TY - CONF AU - Gräßler, Iris AU - Preuß, Daniel AU - Brandt, Lukas AU - Mohr, Michael ID - 46450 T2 - Proceedings of the Design Society TI - Efficient Formalisation of Technical Requirements for Generative Engineering ER - TY - CONF AB - Due to economic and ecological framework conditions, a resource-saving utilization of raw materials and energy is becoming increasingly important in particular in the mobility sector. For the reduction of moving masses and the resources consumed, lightweight construction technologies are part of modern production processes in vehicle manufacturing, for example in the form of multi-material systems. Challenging in the manufacture of multi-material systems especially in view of changing supply chains is the variety of materials and geometries that bring conventional joining processes to their limits. Therefore, new processes are required, which can react versatile to process and disturbance variables. A widely used industrial joining process is semi-tubular self-piercing riveting, which is however a rigid process. To increase the versatility, the two newly established processes multi-range self-piercing riveting and tumbling self-piercing riveting are combined and the capabilities for targeted material flow control are united. Therefore, an innovative two-stage process based on the combination is introduced in this paper. The rivet is set with the multi-range self-piercing riveting process with an overlap of the rivet head and then formed by a tumbling process. Further, a specific adaptation of the tumbling strategy is used to investigate the possibility of reducing cracks in the rivet head. Thereby, different tumbling strategies are used and similar geometric joint formations are achieved to compare the results. AU - Wituschek, Simon AU - Kappe, Fabian AU - Meschut, Gerson AU - Lechner, Michael ID - 52821 SN - 2474-395X T2 - Materials Research Proceedings TI - Combination of versatile self-piercing riveting processes ER - TY - CHAP AU - de Camargo e Souza Câmara, Igor AU - Turhan, Anni-Yasmin ID - 52859 SN - 0302-9743 T2 - Logics in Artificial Intelligence TI - Deciding Subsumption in Defeasible $$\mathcal {ELI}_\bot $$ with Typicality Models ER - TY - JOUR AU - Gil, Oliver Fernández AU - Patrizi, Fabio AU - Perelli, Giuseppe AU - Turhan, Anni-Yasmin ID - 52861 JF - CoRR TI - Optimal Alignment of Temporal Knowledge Bases VL - abs/2307.15439 ER - TY - THES AB - The importance of fiber-reinforced plastics for lightweight construction applications is steadily increasing due to their outstanding weight-specific property values. However, a decisive disadvantage of these composite materials has so far been the high material and process costs, which is why fiber-reinforced plastics are almost exclusively used in small to medium-sized series. Optimization of manufacturing methods is of great importance to reduce the production cost. In this study, two concepts are proposed that can optimize vacuum assisted light resin transfer molding (VA-LRTM) further, leading to a possibility of fully automatic process. Conventional VA-LRTM methods are used to produce complex fiber-reinforced plastics (FRP) and hybrid components. Traditional molds used to produce components via VA-LRTM are sealed using polymer materials to prevent the leakage of matrix system. The seals undergo tremendous amounts of thermal, chemical, and mechanical loadings. Thus, sealings must be replaced in short intervals. In the current study, a concept where sealing is achieved by accelerating the curing of matrix system itself with the help of heating elements and catalysts resulting in a self-sealing approach is proposed. Another concern is mold surface contamination during component production. To address this, a modified automatic cleaning technique based on ultrasonic cleaning was proposed which can be integrated into the production line with minimum modification. Both the proposed concepts were validated and optimized using experiments, simulations, and analytical approaches by producing metal-FRP hybrid shafts. AU - Chalicheemalapalli Jayasankar, Deviprasad ID - 50449 KW - fiber-reinforced plastics KW - resin transfer molding KW - composites TI - Advances In RTM Manufacturing Of Metal-FRP Hybrids By Self-Sealing And In-Mold Cleaning Techniques ER -