@incollection{CzarneckiBensberg2019, author = {Czarnecki, Christian and Bensberg, Frank}, title = {Telekommunikationsunternehmen, Anwendungssysteme f{\"u}r}, series = {Enzyklop{\"a}die der Wirtschaftsinformatik}, booktitle = {Enzyklop{\"a}die der Wirtschaftsinformatik}, publisher = {Gito}, address = {Berlin}, pages = {1 -- 3}, year = {2019}, language = {de} } @incollection{Czarnecki2019, author = {Czarnecki, Christian}, title = {Robotergesteuerte Prozessautomatisierung}, series = {Enzyklop{\"a}die der Wirtschaftsinformatik}, booktitle = {Enzyklop{\"a}die der Wirtschaftsinformatik}, publisher = {Gito}, address = {Berlin}, pages = {1 -- 3}, year = {2019}, language = {de} } @incollection{StengerAltherrAbel2019, author = {Stenger, David and Altherr, Lena and Abel, Dirk}, title = {Machine learning and metaheuristics for black-box optimization of product families: a case-study investigating solution quality vs. computational overhead}, series = {Operations Research Proceedings 2018}, booktitle = {Operations Research Proceedings 2018}, publisher = {Springer}, address = {Cham}, isbn = {978-3-030-18499-5 (Print)}, doi = {10.1007/978-3-030-18500-8_47}, pages = {379 -- 385}, year = {2019}, abstract = {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.}, language = {en} } @incollection{LeiseAltherrSimonetal.2019, author = {Leise, Philipp and Altherr, Lena and Simon, Nicolai and Pelz, Peter F.}, title = {Finding global-optimal gearbox designs for battery electric vehicles}, series = {Optimization of complex systems - theory, models, algorithms and applications : WCGO 2019}, booktitle = {Optimization of complex systems - theory, models, algorithms and applications : WCGO 2019}, publisher = {Springer}, address = {Cham}, isbn = {978-3-030-21802-7}, doi = {10.1007/978-3-030-21803-4_91}, pages = {916 -- 925}, year = {2019}, abstract = {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.}, language = {en} } @incollection{CzarneckiBensberg2019, author = {Czarnecki, Christian and Bensberg, Frank}, title = {Enhanced Telecom Operations Map (eTOM)}, series = {Enzyklop{\"a}die der Wirtschaftsinformatik}, booktitle = {Enzyklop{\"a}die der Wirtschaftsinformatik}, publisher = {Gito}, address = {Berlin}, pages = {1 -- 4}, year = {2019}, language = {de} } @incollection{SchmitzDietzeCzarnecki2019, author = {Schmitz, Manfred and Dietze, Christian and Czarnecki, Christian}, title = {Enabling digital transformation through robotic process automation at Deutsche Telekom}, series = {Enabling digital transformation through robotic process automation at Deutsche Telekom}, booktitle = {Enabling digital transformation through robotic process automation at Deutsche Telekom}, editor = {Urbach, Nils and R{\"o}glinger, Maximilian}, publisher = {Springer}, address = {Cham}, isbn = {978-3-319-95272-7}, doi = {10.1007/978-3-319-95273-4_2}, pages = {15 -- 33}, year = {2019}, abstract = {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.}, language = {en} } @incollection{AuthCzarneckiBensbergetal.2019, author = {Auth, Gunnar and Czarnecki, Christian and Bensberg, Frank and Thor, Andreas}, title = {Digitalisierung des Forschungsprozesses aus Sicht von Forschenden - durch Serviceintegration zum pers{\"o}nlichen Forschungsinformationssystem}, series = {Hochschulen in Zeiten der Digitalisierung : Lehre, Forschung und Organisation}, booktitle = {Hochschulen in Zeiten der Digitalisierung : Lehre, Forschung und Organisation}, editor = {Barton, Thomas and M{\"u}ller, Christian and Seel, Christian}, publisher = {Springer Vieweg}, address = {Wiesbaden}, isbn = {978-3-658-26617-2 (Print)}, doi = {10.1007/978-3-658-26618-9_17}, pages = {287 -- 307}, year = {2019}, abstract = {In der Diskussion {\"u}ber die Digitalisierung der Forschung spielt die Frage nach der optimalen IT-Unterst{\"u}tzung f{\"u}r Forschende eine wichtige Rolle. Forschende k{\"o}nnen heute an ihren Hochschulen bzw. Wissenschaftseinrichtungen auf ein breites Angebot interner IT-Dienstleistungen zur{\"u}ckgreifen, das auch kooperative IT-Dienste umfasst, die von mehreren Institutionen in Zusammenarbeit bereitgestellt werden. Außerhalb der eigenen Organisation und des weiteren Verbunds hat sich im Internet zudem ein breites externes Angebot an innovativen, h{\"a}ufig kostenlos nutzbaren Onlinediensten entwickelt. Neben horizontalen Onlinediensten, die sich prinzipiell an jeden Internetnutzer richten (bspw. Dropbox, Twitter, WhatsApp), nimmt auch die Zahl von vertikalen Diensten f{\"u}r wissenschaftliche bzw. Forschungszwecke immer weiter zu (bspw. GoogleScholar, ResearchGate, figshare). F{\"u}r Forschende er{\"o}ffnen sich damit vielf{\"a}ltige neue M{\"o}glichkeiten, ihren individuellen Forschungsprozess durch digitale Werkzeuge zu verbessern. Aufgrund rechtlicher, technischer und personeller Restriktionen k{\"o}nnen jedoch interne Dienstleister bei der Identifizierung, Auswahl und Nutzung externer Onlinedienste nur wenig Unterst{\"u}tzung leisten. Aus einer serviceorientierten Perspektive stehen Forschende zunehmend vor dem Problem, wie sich heterogene IT-Dienste interner und externer Anbieter in den eigenen Forschungsprozess integrieren lassen. Als L{\"o}sungsansatz skizziert das Kapitel das Konzept eines pers{\"o}nlichen Forschungsinformationssystems nach Gesichtspunkten eines digitalen Servicesystems.}, language = {de} } @incollection{BensbergBuscherCzarnecki2019, author = {Bensberg, Frank and Buscher, Gandalf and Czarnecki, Christian}, title = {Digital transformation and IT topics in the consulting industry: a labor market perspective}, series = {Advances in consulting research : recent findings and practical cases}, booktitle = {Advances in consulting research : recent findings and practical cases}, editor = {Nissen, Volker}, publisher = {Springer}, address = {Cham}, isbn = {978-3-319-95998-6}, doi = {10.1007/978-3-319-95999-3_16}, pages = {341 -- 357}, year = {2019}, abstract = {Information technologies, such as big data analytics, cloud computing, cyber physical systems, robotic process automation, and the internet of things, provide a sustainable impetus for the structural development of business sectors as well as the digitalization of markets, enterprises, and processes. Within the consulting industry, the proliferation of these technologies opened up the new segment of digital transformation, which focuses on setting up, controlling, and implementing projects for enterprises from a broad range of sectors. These recent developments raise the question, which requirements evolve for IT consultants as important success factors of those digital transformation projects. Therefore, this empirical contribution provides indications regarding the qualifications and competences necessary for IT consultants in the era of digital transformation from a labor market perspective. On the one hand, this knowledge base is interesting for the academic education of consultants, since it supports a market-oriented design of adequate training measures. On the other hand, insights into the competence requirements for consultants are considered relevant for skill and talent management processes in consulting practice. Assuming that consulting companies pursue a strategic human resource management approach, labor market information may also be useful to discover strategic behavioral patterns.}, language = {en} } @incollection{RaoPathroseHueningetal.2019, author = {Rao, Deepak and Pathrose, Plato and H{\"u}ning, Felix and Sid, Jithin}, title = {An Approach for Validating Safety of Perception Software in Autonomous Driving Systems}, series = {Model-Based Safety and Assessment: 6th International Symposium, IMBSA 2019, Thessaloniki, Greece, October 16-18, 2019, Proceedings}, booktitle = {Model-Based Safety and Assessment: 6th International Symposium, IMBSA 2019, Thessaloniki, Greece, October 16-18, 2019, Proceedings}, publisher = {Springer}, address = {Cham}, isbn = {978-3-030-32872-6}, doi = {10.1007/978-3-030-32872-6_20}, pages = {303 -- 316}, year = {2019}, abstract = {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.}, language = {en} }