@inproceedings{SildatkeKarwanniKraftetal.2020, author = {Sildatke, Michael and Karwanni, Hendrik and Kraft, Bodo and Schmidts, Oliver and Z{\"u}ndorf, Albert}, title = {Automated Software Quality Monitoring in Research Collaboration Projects}, series = {ICSEW'20: Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops}, booktitle = {ICSEW'20: Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops}, publisher = {IEEE}, address = {New York, NY}, doi = {10.1145/3387940.3391478}, pages = {603 -- 610}, year = {2020}, abstract = {In collaborative research projects, both researchers and practitioners work together solving business-critical challenges. These projects often deal with ETL processes, in which humans extract information from non-machine-readable documents by hand. AI-based machine learning models can help to solve this problem. Since machine learning approaches are not deterministic, their quality of output may decrease over time. This fact leads to an overall quality loss of the application which embeds machine learning models. Hence, the software qualities in development and production may differ. Machine learning models are black boxes. That makes practitioners skeptical and increases the inhibition threshold for early productive use of research prototypes. Continuous monitoring of software quality in production offers an early response capability on quality loss and encourages the use of machine learning approaches. Furthermore, experts have to ensure that they integrate possible new inputs into the model training as quickly as possible. In this paper, we introduce an architecture pattern with a reference implementation that extends the concept of Metrics Driven Research Collaboration with an automated software quality monitoring in productive use and a possibility to auto-generate new test data coming from processed documents in production. Through automated monitoring of the software quality and auto-generated test data, this approach ensures that the software quality meets and keeps requested thresholds in productive use, even during further continuous deployment and changing input data.}, language = {en} } @inproceedings{TamaldinEschTonolietal.2020, author = {Tamaldin, Noreffendy and Esch, Thomas and Tonoli, Andrea and Reisinger, Karl Heinz and Sprenger, Hanna and Razuli, Hisham}, title = {ERASMUS+ United CBHE Automotive International Collaboration from European to South East Asia}, series = {Proceedings of the 2nd African International Conference on Industrial Engineering and Operations Management}, booktitle = {Proceedings of the 2nd African International Conference on Industrial Engineering and Operations Management}, publisher = {IEOM Society International}, address = {Southfield}, isbn = {978-1-7923-6123-4}, issn = {2169-8767}, pages = {2970 -- 2972}, year = {2020}, abstract = {The industrial revolution especially in the IR4.0 era have driven many states of the art technologies to be introduced. The automotive industry as well as many other key industries have also been greatly influenced. The rapid development of automotive industries in Europe have created wide industry gap between European Union (EU) and developing countries such as in South East Asia (SEA). Indulging this situation, FH JOANNEUM, Austria together with European partners from FH Aachen, Germany and Politecnico di Torino, Italy are taking initiative to close down the gap utilizing the Erasmus+ United Capacity Building in Higher Education grant from EU. A consortium was founded to engage with automotive technology transfer using the European framework to Malaysian, Indonesian and Thailand Higher Education Institutions (HEI) as well as automotive industries in respective countries. This could be achieved by establishing Engineering Knowledge Transfer Unit (EKTU) in respective SEA institutions guided by the industry partners in their respective countries. This EKTU could offer updated, innovative and high-quality training courses to increase graduate's employability in higher education institutions and strengthen relations between HEI and the wider economic and social environment by addressing University-industry cooperation which is the regional priority for Asia. It is expected that, the Capacity Building Initiative would improve the quality of higher education and enhancing its relevance for the labor market and society in the SEA partners. The outcome of this project would greatly benefit the partners in strong and complementary partnership targeting the automotive industry and enhanced larger scale international cooperation between the European and SEA partners. It would also prepare the SEA HEI in sustainable partnership with Automotive industry in the region as a mean of income generation in the future.}, language = {en} } @inproceedings{SattlerChicoCaminosAttietal.2020, author = {Sattler, Johannes Christoph and Chico Caminos, Ricardo Alexander and Atti, Vikrama Nagababu and {\"U}rlings, Nicolas and Dutta, Siddharth and Ruiz, Victor and Kalogirou, Soteris and Ktistis, Panayiotis and Agathokleous, Rafaela and Alexopoulos, Spiros and Teixeira Boura, Cristiano Jos{\´e} and Herrmann, Ulf}, title = {Dynamic simulation tool for a performance evaluation and sensitivity study of a parabolic trough collector system with concrete thermal energy storage}, series = {AIP Conference Proceedings 2303}, booktitle = {AIP Conference Proceedings 2303}, publisher = {American Institute of Physics}, address = {Melville, NY}, issn = {0094-243X}, doi = {10.1063/5.0029277}, pages = {160004}, year = {2020}, language = {de} } @inproceedings{Laack2020, author = {Laack, Walter van}, title = {Schnittstelle Tod: Aufbruch oder Ende - Kontakte oder Hirngespinste?}, publisher = {van Laack GmbH}, address = {Aachen}, isbn = {978-3-936624-51-9}, pages = {264 Seiten}, year = {2020}, abstract = {Tagungsbeitr{\"a}ge des 6. Europ{\"a}ischen Seminars am 09. November 2019 in Aachen zum Thema Nahtoderfahrungen mit dem Serientitel: "Schnittstelle Tod"}, language = {de} } @inproceedings{EltesterFerreinSchiffer2020, author = {Eltester, Niklas Sebastian and Ferrein, Alexander and Schiffer, Stefan}, title = {A smart factory setup based on the RoboCup logistics league}, series = {2020 IEEE Conference on Industrial Cyberphysical Systems (ICPS)}, booktitle = {2020 IEEE Conference on Industrial Cyberphysical Systems (ICPS)}, publisher = {IEEE}, address = {New York, NY}, doi = {10.1109/ICPS48405.2020.9274766}, pages = {297 -- 302}, year = {2020}, abstract = {In this paper we present SMART-FACTORY, a setup for a research and teaching facility in industrial robotics that is based on the RoboCup Logistics League. It is driven by the need for developing and applying solutions for digital production. Digitization receives constantly increasing attention in many areas, especially in industry. The common theme is to make things smart by using intelligent computer technology. Especially in the last decade there have been many attempts to improve existing processes in factories, for example, in production logistics, also with deploying cyber-physical systems. An initiative that explores challenges and opportunities for robots in such a setting is the RoboCup Logistics League. Since its foundation in 2012 it is an international effort for research and education in an intra-warehouse logistics scenario. During seven years of competition a lot of knowledge and experience regarding autonomous robots was gained. This knowledge and experience shall provide the basis for further research in challenges of future production. The focus of our SMART-FACTORY is to create a stimulating environment for research on logistics robotics, for teaching activities in computer science and electrical engineering programmes as well as for industrial users to study and explore the feasibility of future technologies. Building on a very successful history in the RoboCup Logistics League we aim to provide stakeholders with a dedicated facility oriented at their individual needs.}, language = {en} }