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In many instances, freight vehicles exchange load or information with plants that are or will soon be Industry4.0 plants. The Wagon4.0 concept, as developed in close cooperation with e.g. port or mine operations, offers a maximum in railway operational efficiency while providing strong business cases already in the respective plant interaction. The Wagon4.0 consists of main components, a power supply, data network, sensors, actuators and an operating system, the so called WagonOS. The Wagon OS is implemented in a granular, self-sufficient manner, to allow basic features such as WiFi-Mesh and train christening in remote areas without network connection. Furthermore, the granularity of the operating system allows to extend the familiar app concept to freight rail rolling stock, making it possible to use specialised actuators for certain applications, e.g. an electrical parking brake or an auxiliary drive. In order to facilitate migration to the Wagon4.0 for existing fleets, a migration concept featuring five levels of technical adaptation was developed. The present paper investigates the benefits of Wagon4.0-implementations for the particular challenges of heavy haul operations by focusing on train christening, ep-assisted braking, autonomous last mile and traction boost operation as well as improved maintenance schedules
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.
Masonry infill walls are commonly used in reinforced concrete (RC) frame structures, also in seismically active areas, although they often experience serious damage during earthquakes. One of the main reasons for their poor behaviour is the connection to the frame, which is usually constructed using mortar. This paper describes the novel solution for infill/frame connection based on application of elastomeric material between them. The system called INODIS (Innovative Decoupled Infill System) has the aim to postpone the activation of infill in in-plane direction and at the same time to provide sufficient out-of-plane support. First, experimental tests on infilled frame specimens are presented and the comparison of the results between traditionally infilled frames and infilled frames with the INODIS system are given. The results are then used for calibration and validation of numerical model, which can be further employed for investigating the influence of some material parameters on the behaviour of infilled frames with the INODIS system.
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.
Diversity is increasingly being addressed as an innovation-promoting factor. For this reason, companies and institutions tackle the integration of a diversity management approach that enables a heterogenic perspective on innovation development. However, system-theoretical frameworks state that the implementation of diversity measures that are not tailored to the needs of the organization often leads to a rejection or reactivity with regard to the management approach. In this context, especially organizations, which are characterized by a specific hierarchical structure, a dominant habitus or specialist culture, must face the challenge of realizing a sustainable change of the corporate culture that sets the basis for implementing diversity management approaches. The presented research project focuses on analyzing the situation in a huge scientific collaborative project - so called Cluster of Excellence (CoE) - with the aim to implement a diversity - and innovation management strategy. Considering the influencing determinants, the CoE is characterized by its embeddedness in the scientific system, a complex organizational structure, and a high fluctuation rate. The paper presents a systemic approach of reflecting these factors in order to develop a diversity- and innovation management strategy. In this frame, the results of a quantitative survey of CoE employees and derived mindset-types are presented. The results show a need for taking different mindset-types into account, to be able to develop a tailored management strategy. The aim of the project is to give recommendations for developing a sustainable management concept that promotes both diversity and innovation by drawing on the persisting mindsets of organization members while reflecting top down as well as bottom up factors of implementation processes as well as the psychology of change. This paper addresses all who are concerned with the management of human resources in innovation processes and are striving for a cultural change within the framework of complex organizations.
Asteroid mining has the potential to greatly reduce the cost of in-space manufacturing, production of propellant for space transportation and consumables for crewed spacecraft, compared to launching the required resources from Earth’s deep gravity well. This paper discusses the top-level mission architecture and trajectory design for these resource-return missions, comparing high-thrust trajectories with continuous low-thrust solar-sail trajectories. This work focuses on maximizing the economic Net Present Value, which takes the time-cost of finance into account and therefore balances the returned resource mass and mission duration. The different propulsion methods will then be compared in terms of maximum economic return, sets of attainable target asteroids, and mission flexibility. This paper provides one more step towards making commercial asteroid mining an economically viable reality by integrating trajectory design, propulsion technology and economic modelling.
In parallel to the evolution of the Planetary Defense Conference, the exploration of small solar system bodies has advanced from fast fly-bys on the sidelines of missions to the planets to the implementation of dedicated sample-return and in-situ analysis missions. Spacecraft of all sizes have landed, touch-and-go sampled, been gently beached, or impacted at hypervelocity on asteroid and comet surfaces. More have flown by close enough to image their surfaces in detail or sample their immediate environment, often as part of an extended or re-purposed mission. And finally, full-scale planetary defense experiment missions are in the making. Highly efficient low-thrust propulsion is increasingly applied beyond commercial use also in mainstream and flagship science missions, in combination with gravity assist propulsion. Another development in the same years is the growth of small spacecraft solutions, not in size but in numbers and individual capabilities. The on-going NASA OSIRIS-REx and JAXA HAYABUSA2 missions exemplify the trend as well as the upcoming NEA SCOUT mission or the landers MINERVA-II and MASCOT recently deployed on Ryugu. We outline likely as well as possible and efficient routes of continuation of all these developments towards a propellant-less and highly efficient class of spacecraft for small solar system body exploration: small spacecraft solar sails designed for carefree handling and equipped with carried landers and application modules, for all asteroid user communities –planetary science, planetary defence, and in-situ resource utilization. This projection builds on the experience gained in the development of deployable membrane structures leading up to the successful ground deployment test of a (20 m)² solar sail at DLR Cologne and in the 20 years since. It draws on the background of extensive trajectory optimization studies, the qualified technology of the DLR GOSSAMER-1 deployment demonstrator, and the MASCOT asteroid lander. These enable ‘now-term’ as well as near-term hardware solutions, and thus responsive fast-paced development. Mission types directly applicable to planetary defense include: single and Multiple NEA Rendezvous ((M)NR) for mitigation precursor, target monitoring and deflection follow-up tasks; sail-propelled head-on retrograde kinetic impactors (RKI) for mitigation; and deployable membrane based methods to modify the asteroid’s properties or interact with it. The DLR-ESTEC GOSSAMER Roadmap initiated studies of missions uniquely feasible with solar sails such as Displaced L1 (DL1) space weather advance warning and monitoring and Solar Polar Orbiter (SPO) delivery which demonstrate the capability of near-term solar sails to achieve NEA rendezvous in any kind of orbit, from Earth-coorbital to extremely inclined and even retrograde orbits. For those mission types using separable payloads, such as SPO, (M)NR and RKI, design concepts can be derived from the separable Boom Sail Deployment Units characteristic of DLR GOSSAMER solar sail technology, nanolanders like MASCOT, or microlanders like the JAXA-DLR Jupiter Trojan Asteroid Lander for the OKEANOS mission which can shuttle from the sail to the asteroids visited and enable multiple NEA sample-return missions. These are an ideal match for solar sails in micro-spacecraft format whose launch configurations are compatible with ESPA and ASAP secondary payload platforms.
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.