Fachbereich Maschinenbau und Mechatronik
Refine
Year of publication
Institute
- Fachbereich Maschinenbau und Mechatronik (280)
- MASKOR Institut für Mobile Autonome Systeme und Kognitive Robotik (19)
- ECSM European Center for Sustainable Mobility (4)
- Fachbereich Elektrotechnik und Informationstechnik (4)
- Fachbereich Luft- und Raumfahrttechnik (3)
- IaAM - Institut für angewandte Automation und Mechatronik (2)
- Fachbereich Chemie und Biotechnologie (1)
- Fachbereich Medizintechnik und Technomathematik (1)
- IfB - Institut für Bioengineering (1)
Language
- English (280) (remove)
Document Type
- Article (149)
- Conference Proceeding (107)
- Book (8)
- Part of a Book (8)
- Lecture (3)
- Bachelor Thesis (1)
- Contribution to a Periodical (1)
- Doctoral Thesis (1)
- Master's Thesis (1)
- Report (1)
Keywords
- Additive manufacturing (4)
- Gamification (4)
- additive manufacturing (3)
- Actuators (2)
- Additive Manufacturing (2)
- Aktor (2)
- Aktoren (2)
- Brake set-up (2)
- Digital Twin (2)
- Freight rail (2)
During the development process of a complex technical product, one widely used and important technique is accelerated testing where the applied stress on a component is chosen to exceed the reference stress, i.e. the stress encountered in field operation, in order to reduce the time to failure. For that, the reference stress has to be known. Since a complex technical product may fail regarding numerous failure modes, stress in general is highly dimensional rather than scalar. In addition, customers use their products individually, i.e. field operation should be described by a distribution rather than by one scalar stress value. In this paper, a way to span the customer usage space is shown. It allows the identification of worst case reference stress profiles in significantly reduced dimensions with minimal loss of information. The application example shows that even for a complex product like a combustion engine, stress information can be compressed significantly. With low measurement effort it turned out that only three reference stress cycles were sufficient to cover a broad range of customer stress variety.
In competition with other modes of transport, rail freight transport is looking for solutions to become more attractive. Short-term success can be achieved through the data-driven optimization of operations and maintenance as well as the application of novel strategies such as prescriptive maintenance. After introducing the concept of prescriptive maintenance, this paper aims to prove that vehicle-focused applications of this approach indeed have the potential to increase attractiveness. However, even greater advantages can be activated if data from the horizontal network of the vehicle is available. Drawing on the state of the art in research and technology in the field of cyber-physical systems (CPS) as well as digital twins and shadows, our work serves to design a system of systems for the horizontal interconnection of a rail vehicle and to conceptualize a draft for a digital twin of a locomotive.
Hands-on-training in high technology areas is usually limited due to the high cost for lab infrastructure and equipment. One specific example is the field of MEMS, where investment and upkeep of clean rooms with microtechnology equipment is either financed by production or R&D projects greatly reducing the availability for education purposes. For efficient hands-on-courses a MEMS training foundry, currently used jointly by six higher education institutions, was established at FH Kaiserslautern. In a typical one week course, students manufacture a micromachined pressure sensor including all lithography, thin film and packaging steps. This compact and yet complete program is only possible because participants learn to use the different complex machines in advance via a Virtual Training Lab (VTL). In this paper we present the concept of the MEMS training foundry and the VTL preparation together with results from a scientific evaluation of the VTL over the last three years.