TY - CHAP A1 - Pieronek, Lukas A1 - Kleefeld, Andreas ED - Constanda, Christian ED - Harris, Paul T1 - The Method of Fundamental Solutions for Computing Interior Transmission Eigenvalues of Inhomogeneous Media T2 - Integral Methods in Science and Engineering: Analytic Treatment and Numerical Approximations N2 - The method of fundamental solutions is applied to the approximate computation of interior transmission eigenvalues for a special class of inhomogeneous media in two dimensions. We give a short approximation analysis accompanied with numerical results that clearly prove practical convenience of our alternative approach. Y1 - 2019 SN - 978-3-030-16077-7 U6 - https://doi.org/10.1007/978-3-030-16077-7_28 SP - 353 EP - 365 PB - Birkhäuser CY - Cham ER - TY - CHAP A1 - Rao, Deepak A1 - Pathrose, Plato A1 - Hüning, Felix A1 - Sid, Jithin T1 - An Approach for Validating Safety of Perception Software in Autonomous Driving Systems T2 - Model-Based Safety and Assessment: 6th International Symposium, IMBSA 2019, Thessaloniki, Greece, October 16–18, 2019, Proceedings N2 - The increasing complexity of Advanced Driver Assistance Systems (ADAS) presents a challenging task to validate safe and reliable performance of these systems under varied conditions. The test and validation of ADAS/AD with real test drives, although important, involves huge costs and time. Simulation tools provide an alternative with the added advantage of reproducibility but often use ideal sensors, which do not reflect real sensor output accurately. This paper presents a new validation methodology using fault injection, as recommended by the ISO 26262 standard, to test software and system robustness. In our work, we investigated and developed a tool capable of inserting faults at different software and system levels to verify its robustness. The scope of this paper is to cover the fault injection test for the Visteon’s DriveCore™ system, a centralized domain controller for Autonomous driving which is sensor agnostic and SoC agnostic. With this new approach, the validation of safety monitoring functionality and its behavior can be tested using real-world data instead of synthetic data from simulation tools resulting in having better confidence in system performance before proceeding with in-vehicle testing. KW - Advanced driver assistance systems (ADAS/AD) KW - ISO 26262 KW - Safety-critical systems validation KW - Safety of the intended functionality (SOTIF) Y1 - 2019 SN - 978-3-030-32872-6 U6 - https://doi.org/10.1007/978-3-030-32872-6_20 SP - 303 EP - 316 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 - https://doi.org/10.1007/978-3-319-95273-4_2 SP - 15 EP - 33 PB - Springer CY - Cham 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 - https://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 - https://doi.org/10.1007/10_2017_58 N1 - Advances in biochemical engineering/biotechnology ; Vol. 166 SP - 43 EP - 68 PB - Springer CY - Cham ER -