Conference Proceeding
Refine
Year of publication
- 2019 (94) (remove)
Institute
- Fachbereich Luft- und Raumfahrttechnik (25)
- Fachbereich Elektrotechnik und Informationstechnik (24)
- Fachbereich Maschinenbau und Mechatronik (13)
- IfB - Institut für Bioengineering (12)
- Fachbereich Medizintechnik und Technomathematik (11)
- Fachbereich Energietechnik (8)
- MASKOR Institut für Mobile Autonome Systeme und Kognitive Robotik (7)
- Fachbereich Bauingenieurwesen (5)
- Fachbereich Wirtschaftswissenschaften (5)
- Solar-Institut Jülich (5)
Document Type
- Conference Proceeding (94) (remove)
Keywords
- Enterprise Architecture (2)
- Aircraft design (1)
- Case Study (1)
- Change Management (1)
- Corporate Culture (1)
- Correlations (1)
- Design rules (1)
- Digital Age (1)
- Digitalisierung (1)
- Diversity Management (1)
Neue Perspektiven für die Bahn in der Produktions- und Distributionslogistik durch Prozessautomation
(2019)
Deutschland braucht mehr Eisenbahn um CO2-Emissionen aus dem Verkehr zu reduzieren. Sie muss zum Rückgrat aktueller Logistikprozesse, z.B. bei Kaufmannsgütern und E-Commerce, werden. Dies geht nicht ohne neuartige betriebliche Konzepte und eine Transformation des Güterwagens von einem „dummen Stück Stahl“ zu einem modernen Werkzeug der Logistik.
Als „Güterwagen 4.0“ wird ein kommunikativer und kooperativer Güterwagen verstanden, der die Voraussetzung zur Automatisierung aller Prozesse der Zugvorbereitung bereitstellt, sich aber ansonsten vollkommen kompatibel mit heutigen Betriebsverfahren im Hauptlauf präsentiert. Durch Kommunikation zwischen Güterwagen und umgebenden intelligenten Systemen im Sinne eines „Internet der Dinge“ gelingt damit unter Anderem die Realisierung hoch effizienter Gleisanschlussverkehre, die der Güterbahn neue Märkte abseits der klassisch bahn-affinen Verkehre erschließen und letztlich den Wandel zu einer nachhaltigen Gütermobilität fördern.
The paper industry is the industry with the third highest energy consumption in the European Union. Using recycled paper instead of fresh fibers for papermaking is less energy consuming and saves resources. However, adhesive contaminants in recycled paper are particularly problematic since they reduce the quality of the resulting paper-product. To remove as many contaminants and at the same time obtain as many valuable fibres as possible, fine screening systems, consisting of multiple interconnected pressure screens, are used. Choosing the best configuration is a non-trivial task: The screens can be interconnected in several ways, and suitable screen designs as well as operational parameters have to be selected. Additionally, one has to face conflicting objectives. In this paper, we present an approach for the multi-criteria optimization of pressure screen systems based on Mixed-Integer Nonlinear Programming. We specifically focus on a clear representation of the trade-off between different objectives.
Human induced pluripotent stem cells (hiPSCs) have shown to be promising in disease studies and drug screenings [1]. Cardiomyocytes derived from hiPSCs have been extensively investigated using patch-clamping and optical methods to compare their electromechanical behaviour relative to fully matured adult cells. Mathematical models can be used for translating findings on hiPSCCMs to adult cells [2] or to better understand the mechanisms of various ion channels when a drug is applied [3,4]. Paci et al. (2013) [3] developed the first model of hiPSC-CMs, which they later refined based on new data [3]. The model is based on iCells® (Fujifilm Cellular Dynamics, Inc. (FCDI), Madison WI, USA) but major differences among several cell lines and even within a single cell line have been found and motivate an approach for creating sample-specific models. We have developed an optimisation algorithm that parameterises the conductances (in S/F=Siemens/Farad) of the latest Paci et al. model (2018) [5] using current-voltage data obtained in individual patch-clamp experiments derived from an automated patch clamp system (Patchliner, Nanion Technologies GmbH, Munich).
MedicVR : Acceleration and Enhancement Techniques for Direct Volume Rendering in Virtual Reality
(2019)
Manufacturing Process Simulation for the Prediction of Tool-Part-Interaction and Ply Wrinkling
(2019)
Die steigende Popularität von mobilen Endgeräten im privaten und geschäftlichen Umfeld geht mit einem Anstieg an Sicherheitslücken und somit potentiellen Angriffsflächen einher. Als ein Element der technischen und organisatorischen Maßnahmen zum Schutz eines Netzwerkes können Monitoring-Apps dienen, die unerwünschtes Verhalten und Angriffe erkennen. Die automatisierte Überwachung von Endgeräten ist jedoch rechtlich und ethisch komplex. Dies in Kombination mit einer hohen Sensibilität der Nutzer und Nutzerinnen dieser Geräte in Bezug auf Privatsphäre, kann zu einer geringen Akzeptanz und Compliance führen. Eine datenschutzrechtlich und ethisch einwandfreie Konzeption solcher Apps bereits im Designprozess führt zu höherer Akzeptanz und verbessert so die Effizienz. Diese Analyse beschreibt Möglichkeiten zur Umsetzung.
Effective training requires high muscle forces potentially leading to training-induced injuries. Thus, continuous monitoring and controlling of the loadings applied to the musculoskeletal system along the motion trajectory is required. In this paper, a norm-optimal iterative learning control algorithm for the robot-assisted training is developed. The algorithm aims at minimizing the external knee joint moment, which is commonly used to quantify the loading of the medial compartment. To estimate the external knee joint moment, a musculoskeletal lower extremity model is implemented in OpenSim and coupled with a model of an industrial robot and a force plate mounted at its end-effector. The algorithm is tested in simulation for patients with varus, normal and valgus alignment of the knee. The results show that the algorithm is able to minimize the external knee joint moment in all three cases and converges after less than seven iterations.
Improved efficiency prediction of a molten salt receiver based on dynamic cloud passage simulation
(2019)
The initial idea of Robotic Process Automation (RPA) is the automation of business processes through the presentation layer of existing application systems. For this simple emulation of user input and output by software robots, no changes of the systems and architecture is required. However, considering strategic aspects of aligning business and technology on an enterprise level as well as the growing capabilities of RPA driven by artificial intelligence, interrelations between RPA and Enterprise Architecture (EA) become visible and pose new questions. In this paper we discuss the relationship between RPA and EA in terms of perspectives and implications. As workin- progress we focus on identifying new questions and research opportunities related to RPA and EA.