TY - CHAP A1 - Franzen, Julian A1 - Stecken, Jannis A1 - Pfaff, Raphael A1 - Kuhlenkötter, Bernd T1 - Using the Digital Shadow for a Prescriptive Optimization of Maintenance and Operation : The Locomotive in the Context of the Cyber-Physical System T2 - Advances in Production, Logistics and Traffic N2 - 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. Y1 - 2019 SN - 978-3-030-13535-5 U6 - http://dx.doi.org/10.1007/978-3-030-13535-5_19 SP - 265 EP - 276 PB - Springer CY - Cham ER - TY - CHAP A1 - Ernhardt, Selina A1 - Drumm, Christian A1 - van Gog, Tamara A1 - Brand-Gruwel, Saskia A1 - Jarodzka, Halszka T1 - Through the eyes of a programmer : a research project on how to foster programming education with eye-tracking technology T2 - Tagungsband zur 32. AKWI-Jahrestagung vom 15.09.2019 bis 18.09.2019 an der Fachhochschule für Angewandte Wissenschaften Aachen Y1 - 2019 SN - 978-3-944330-62-4 SP - 42 EP - 47 PB - Mana-Buch CY - Heide ER - TY - CHAP A1 - Meskouris, Konstantin A1 - Butenweg, Christoph A1 - Hinzen, Klaus-G. A1 - Höffer, Rüdiger T1 - Stochasticity of Wind Processes and Spectral Analysis of Structural Gust Response T2 - Structural Dynamics with Applications in Earthquake and Wind Engineering N2 - Wind loads have great impact on many engineering structures. Wind storms often cause irreparable damage to the buildings which are exposed to it. Along with the earthquakes, wind represents one of the most common environmental load on structures and is relevant for limit state design. Modern wind codes indicate calculation procedures allowing engineers to deal with structural systems, which are susceptible to conduct wind-excited oscillations. In the codes approximate formulas for wind buffeting are specified which relate the dynamic problem to rather abstract parameter functions. The complete theory behind is not visible in order to simplify the applicability of the procedures. This chapter derives the underlying basic relations of the spectral method for wind buffeting and explains the main important applications of it in order to elucidate part of the theoretical background of computations after the new codes. The stochasticity of the wind processes is addressed, and the analysis of analytical as well as measurement based power spectra is outlined. Short MATLAB codes are added to the Appendix 3 which carry out the computation of a single sided auto-spectrum from a statistically stationary, discrete stochastic process. Two examples are presented. KW - Wind turbulence KW - Gust wind response KW - Spectral analysis Y1 - 2019 SN - 978-3-662-57550-5 (Online) SN - 978-3-662-57548-2 (Print) U6 - http://dx.doi.org/10.1007/978-3-662-57550-5_3 SP - 153 EP - 196 PB - Springer CY - Berlin ER - TY - CHAP A1 - Butenweg, Christoph A1 - Holtschoppen, Britta T1 - Seismic design of structures and components in industrial units T2 - Structural Dynamics with Applications in Earthquake and Wind Engineering N2 - Industrial units consist of the primary load-carrying structure and various process engineering components, the latter being by far the most important in financial terms. In addition, supply structures such as free-standing tanks and silos are usually required for each plant to ensure the supply of material and product storage. Thus, for the earthquake-proof design of industrial plants, design and construction rules are required for the primary structures, the secondary structures and the supply structures. Within the framework of these rules, possible interactions of primary and secondary structures must also be taken into account. Importance factors are used in seismic design in order to take into account the usually higher risk potential of an industrial unit compared to conventional building structures. Industrial facilities must be able to withstand seismic actions because of possibly wide-ranging damage consequences in addition to losses due to production standstill and the destruction of valuable equipment. The chapter presents an integrated concept for the seismic design of industrial units based on current seismic standards and the latest research results. Special attention is devoted to the seismic design of steel thin-walled silos and tank structures. KW - Industrial units KW - Seismic design KW - Tanks KW - Silos KW - Components Y1 - 2019 SN - 978-3-662-57550-5 U6 - http://dx.doi.org/10.1007/978-3-662-57550-5_5 SP - 359 EP - 481 PB - Springer CY - Berlin ER - TY - CHAP A1 - Gebhardt, Andreas A1 - Hoetter, Jan-Steffen T1 - Rapid Tooling T2 - CIRP Encyclopedia of Production Engineering Y1 - 2019 SN - 978-3-662-53120-4 U6 - http://dx.doi.org/10.1007/978-3-662-53120-4 SP - 39 EP - 52 PB - Springer CY - Berlin, Heidelberg ER - TY - CHAP A1 - Stenger, David A1 - Altherr, Lena A1 - Abel, Dirk T1 - Machine learning and metaheuristics for black-box optimization of product families: a case-study investigating solution quality vs. computational overhead T2 - Operations Research Proceedings 2018 N2 - In product development, numerous design decisions have to be made. Multi-domain virtual prototyping provides a variety of tools to assess technical feasibility of design options, however often requires substantial computational effort for just a single evaluation. A special challenge is therefore the optimal design of product families, which consist of a group of products derived from a common platform. Finding an optimal platform configuration (stating what is shared and what is individually designed for each product) and an optimal design of all products simultaneously leads to a mixed-integer nonlinear black-box optimization model. We present an optimization approach based on metamodels and a metaheuristic. To increase computational efficiency and solution quality, we compare different types of Gaussian process regression metamodels adapted from the domain of machine learning, and combine them with a genetic algorithm. We illustrate our approach on the example of a product family of electrical drives, and investigate the trade-off between solution quality and computational overhead. KW - Product family optimization KW - Mixed-integer nonlinear black-box optimization KW - Engineering optimization KW - Machine learning Y1 - 2019 SN - 978-3-030-18499-5 (Print) SN - 978-3-030-18500-8 (Online) U6 - http://dx.doi.org/10.1007/978-3-030-18500-8_47 SP - 379 EP - 385 PB - Springer CY - Cham ER - TY - CHAP A1 - Tippkötter, Nils A1 - Möhring, Sophie A1 - Roth, Jasmine A1 - Wulfhorst, Helene T1 - Logistics of lignocellulosic feedstocks: preprocessing as a preferable option T2 - Biorefineries N2 - In comparison to crude oil, biorefinery raw materials are challenging in concerns of transport and storage. The plant raw materials are more voluminous, so that shredding and compacting usually are necessary before transport. These mechanical processes can have a negative influence on the subsequent biotechnological processing and shelf life of the raw materials. Various approaches and their effects on renewable raw materials are shown. In addition, aspects of decentralized pretreatment steps are discussed. Another important aspect of pretreatment is the varying composition of the raw materials depending on the growth conditions. This problem can be solved with advanced on-site spectrometric analysis of the material. KW - Analytics KW - Decentral KW - Mechanical KW - On-site KW - Pre-treatment Y1 - 2019 SN - 978-3-319-97117-9 SN - 978-3-319-97119-3 U6 - http://dx.doi.org/10.1007/10_2017_58 N1 - Advances in biochemical engineering/biotechnology ; Vol. 166 SP - 43 EP - 68 PB - Springer CY - Cham ER - TY - CHAP A1 - Dachwald, Bernd A1 - Ohndorf, Andreas T1 - Global optimization of continuous-thrust trajectories using evolutionary neurocontrol T2 - Modeling and Optimization in Space Engineering N2 - Searching optimal continuous-thrust trajectories is usually a difficult and time-consuming task. The solution quality of traditional optimal-control methods depends strongly on an adequate initial guess because the solution is typically close to the initial guess, which may be far from the (unknown) global optimum. Evolutionary neurocontrol attacks continuous-thrust optimization problems from the perspective of artificial intelligence and machine learning, combining artificial neural networks and evolutionary algorithms. This chapter describes the method and shows some example results for single- and multi-phase continuous-thrust trajectory optimization problems to assess its performance. Evolutionary neurocontrol can explore the trajectory search space more exhaustively than a human expert can do with traditional optimal-control methods. Especially for difficult problems, it usually finds solutions that are closer to the global optimum. Another fundamental advantage is that continuous-thrust trajectories can be optimized without an initial guess and without expert supervision. Y1 - 2019 SN - 978-3-030-10501-3 SN - 978-3-030-10500-6 U6 - http://dx.doi.org/10.1007/978-3-030-10501-3_2 N1 - Springer Optimization and Its Applications, vol 144 gedruckt unter der Signatur 21 ZSS 46 in der Bereichsbibliothek Eupener Str. vorhanden SP - 33 EP - 57 PB - Springer CY - Cham ER - TY - CHAP A1 - Leise, Philipp A1 - Altherr, Lena A1 - Simon, Nicolai A1 - Pelz, Peter F. T1 - Finding global-optimal gearbox designs for battery electric vehicles T2 - Optimization of complex systems - theory, models, algorithms and applications : WCGO 2019 N2 - In order to maximize the possible travel distance of battery electric vehicles with one battery charge, it is mandatory to adjust all components of the powertrain carefully to each other. While current vehicle designs mostly simplify the powertrain rigorously and use an electric motor in combination with a gearbox with only one fixed transmission ratio, the use of multi-gear systems has great potential. First, a multi-speed system is able to improve the overall energy efficiency. Secondly, it is able to reduce the maximum momentum and therefore to reduce the maximum current provided by the traction battery, which results in a longer battery lifetime. In this paper, we present a systematic way to generate multi-gear gearbox designs that—combined with a certain electric motor—lead to the most efficient fulfillment of predefined load scenarios and are at the same time robust to uncertainties in the load. Therefore, we model the electric motor and the gearbox within a Mixed-Integer Nonlinear Program, and optimize the efficiency of the mechanical parts of the powertrain. By combining this mathematical optimization program with an unsupervised machine learning algorithm, we are able to derive global-optimal gearbox designs for practically relevant momentum and speed requirements. KW - Powertrain KW - Gearbox KW - Optimization KW - BEV KW - WLTP Y1 - 2019 SN - 978-3-030-21802-7 U6 - http://dx.doi.org/10.1007/978-3-030-21803-4_91 SP - 916 EP - 925 PB - Springer CY - Cham ER - TY - CHAP A1 - Schmitz, Manfred A1 - Dietze, Christian A1 - Czarnecki, Christian ED - Urbach, Nils ED - Röglinger, Maximilian T1 - Enabling digital transformation through robotic process automation at Deutsche Telekom T2 - Enabling digital transformation through robotic process automation at Deutsche Telekom N2 - Due to the high number of customer contacts, fault clearances, installations, and product provisioning per year, the automation level of operational processes has a significant impact on financial results, quality, and customer experience. Therefore, the telecommunications operator Deutsche Telekom (DT) has defined a digital strategy with the objectives of zero complexity and zero complaint, one touch, agility in service, and disruptive thinking. In this context, Robotic Process Automation (RPA) was identified as an enabling technology to formulate and realize DT’s digital strategy through automation of rule-based, routine, and predictable tasks in combination with structured and stable data. Y1 - 2019 SN - 978-3-319-95272-7 U6 - http://dx.doi.org/10.1007/978-3-319-95273-4_2 SP - 15 EP - 33 PB - Springer CY - Cham ER -