TY - CHAP A1 - Philipp, Brauner A1 - Brillowski, Florian Sascha A1 - Dammers, Hannah A1 - Königs, Peter A1 - Kordtomeikel, Frauke Carole A1 - Petruck, Henning A1 - Schaar, Anne Kathrin A1 - Schmitz, Seth A1 - Steuer-Dankert, Linda A1 - Mertens, Alexander A1 - Gries, Thomas A1 - Leicht-Scholten, Carmen A1 - Nagel, Saskia K. A1 - Nitsch, Verena A1 - Schuh, Günther A1 - Ziefle, Martina ED - Mrugalska, Beata ED - Trzcielinski, Stefan ED - Karwowski, Waldemar ED - Nicolantonio, Massimo Di ED - Roossi, Emilio T1 - A research framework for human aspects in the internet of production: an intra-company perspective T2 - Proceedings of the AHFE 2020 N2 - Digitalization in the production sector aims at transferring concepts and methods from the Internet of Things (IoT) to the industry and is, as a result, currently reshaping the production area. Besides technological progress, changes in work processes and organization are relevant for a successful implementation of the “Internet of Production” (IoP). Focusing on the labor organization and organizational procedures emphasizes to consider intra-company factors such as (user) acceptance, ethical issues, and ergonomics in the context of IoP approaches. In the scope of this paper, a research approach is presented that considers these aspects from an intra-company perspective by conducting studies on the shop floor, control level and management level of companies in the production area. Focused on four central dimensions—governance, organization, capabilities, and interfaces—this contribution presents a research framework that is focused on a systematic integration and consideration of human aspects in the realization of the IoP. KW - Human factors KW - Digitalization KW - Acceptance KW - Ethics KW - Human-robot collaboration Y1 - 2020 SN - 978-3-030-51980-3 U6 - https://doi.org/10.1007/978-3-030-51981-0_1 N1 - AHFE 2020 Virtual Conferences on Human Aspects of Advanced Manufacturing, Advanced Production Management and Process Control, and Additive Manufacturing, Modeling Systems and 3D Prototyping, July 16–20, 2020, USA SP - 3 EP - 17 PB - Springer CY - Cham ER - TY - CHAP A1 - Pohle-Fröhlich, Regina A1 - Dalitz, Christoph A1 - Richter, Charlotte A1 - Hahnen, Tobias A1 - Stäudle, Benjamin A1 - Albracht, Kirsten T1 - Estimation of muscle fascicle orientation in ultrasonic images T2 - Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5 N2 - We compare four different algorithms for automatically estimating the muscle fascicle angle from ultrasonic images: the vesselness filter, the Radon transform, the projection profile method and the gray level cooccurence matrix (GLCM). The algorithm results are compared to ground truth data generated by three different experts on 425 image frames from two videos recorded during different types of motion. The best agreement with the ground truth data was achieved by a combination of pre-processing with a vesselness filter and measuring the angle with the projection profile method. The robustness of the estimation is increased by applying the algorithms to subregions with high gradients and performing a LOESS fit through these estimates. Y1 - 2020 SN - 978-989-758-402-2 U6 - https://doi.org/10.5220/0008933900790086 N1 - 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications VISAPP 2020, Valletta, Malta SP - 79 EP - 86 PB - SciTePress CY - Setúbal, Portugal ER - TY - CHAP A1 - Reke, Michael A1 - Peter, Daniel A1 - Schulte-Tigges, Joschua A1 - Schiffer, Stefan A1 - Ferrein, Alexander A1 - Walter, Thomas A1 - Matheis, Dominik T1 - A Self-Driving Car Architecture in ROS2 T2 - 2020 International SAUPEC/RobMech/PRASA Conference, Cape Town, South Africa N2 - In this paper we report on an architecture for a self-driving car that is based on ROS2. Self-driving cars have to take decisions based on their sensory input in real-time, providing high reliability with a strong demand in functional safety. In principle, self-driving cars are robots. However, typical robot software, in general, and the previous version of the Robot Operating System (ROS), in particular, does not always meet these requirements. With the successor ROS2 the situation has changed and it might be considered as a solution for automated and autonomous driving. Existing robotic software based on ROS was not ready for safety critical applications like self-driving cars. We propose an architecture for using ROS2 for a self-driving car that enables safe and reliable real-time behaviour, but keeping the advantages of ROS such as a distributed architecture and standardised message types. First experiments with an automated real passenger car at lower and higher speed-levels show that our approach seems feasible for autonomous driving under the necessary real-time conditions. Y1 - 2020 SN - 978-1-7281-4162-6 U6 - https://doi.org/10.1109/SAUPEC/RobMech/PRASA48453.2020.9041020 N1 - 2020 International SAUPEC/RobMech/PRASA Conference, 29-31 Jan. 2020, Cape Town, South Africa SP - 1 EP - 6 PB - IEEE CY - New York, NY ER - TY - CHAP A1 - Rendon, Carlos A1 - Schwager, Christian A1 - Ghiasi, Mona A1 - Schmitz, Pascal A1 - Bohang, Fakhri A1 - Chico Caminos, Ricardo Alexander A1 - Teixeira Boura, Cristiano José A1 - Herrmann, Ulf T1 - Modeling and upscaling of a pilot bayonettube reactor for indirect solar mixed methane reforming T2 - AIP Conference Proceedings N2 - A 16.77 kW thermal power bayonet-tube reactor for the mixed reforming of methane using solar energy has been designed and modeled. A test bench for the experimental tests has been installed at the Synlight facility in Juelich, Germany and has just been commissioned. This paper presents the solar-heated reactor design for a combined steam and dry reforming as well as a scaled-up process simulation of a solar reforming plant for methanol production. Solar power towers are capable of providing large amounts of heat to drive high-endothermic reactions, and their integration with thermochemical processes shows a promising future. In the designed bayonet-tube reactor, the conventional burner arrangement for the combustion of natural gas has been substituted by a continuous 930 °C hot air stream, provided by means of a solar heated air receiver, a ceramic thermal storage and an auxiliary firing system. Inside the solar-heated reactor, the heat is transferred by means of convective mechanism mainly; instead of radiation mechanism as typically prevailing in fossil-based industrial reforming processes. A scaled-up solar reforming plant of 50.5 MWth was designed and simulated in Dymola® and AspenPlus®. In comparison to a fossil-based industrial reforming process of the same thermal capacity, a solar reforming plant with thermal storage promises a reduction up to 57 % of annual natural gas consumption in regions with annual DNI-value of 2349 kWh/m2. The benchmark solar reforming plant contributes to a CO2 avoidance of approx. 79 kilotons per year. This facility can produce a nominal output of 734.4 t of synthesis gas and out of this 530 t of methanol a day. Y1 - 2020 U6 - https://doi.org/10.1063/5.0029974 N1 - SOLARPACES 2019: International Conference on Concentrating Solar Power and Chemical Energy Systems, 1–4 October 2019, Daegu, South Korea IS - 2303 SP - 170012-1 EP - 170012-9 ER - TY - CHAP A1 - Sattler, Johannes Christoph A1 - Chico Caminos, Ricardo Alexander A1 - Atti, Vikrama Naga Babu A1 - Ürlings, Nicolas A1 - Dutta, Siddharth A1 - Ruiz, Victor A1 - Kalogirou, Soteris A1 - Ktistis, Panayiotis A1 - Agathokleous, Rafaela A1 - Alexopoulos, Spiros A1 - Teixeira Boura, Cristiano José A1 - Herrmann, Ulf T1 - Dynamic simulation tool for a performance evaluation and sensitivity study of a parabolic trough collector system with concrete thermal energy storage T2 - AIP Conference Proceedings 2303 Y1 - 2020 U6 - https://doi.org/10.1063/5.0029277 SN - 0094-243X N1 - SOLARPACES 2019: International Conference on Concentrating Solar Power and Chemical Energy Systems, 1–4 October 2019, Daegu, South Korea SP - 160004 PB - American Institute of Physics CY - Melville, NY ER - TY - CHAP A1 - Sattler, Johannes Christoph A1 - Chico Caminos, Ricardo Alexander A1 - Ürlings, Nicolas A1 - Dutta, Siddharth A1 - Ruiz, Victor A1 - Kalogirou, Soteris A1 - Ktistis, Panayiotis A1 - Agathokleous, Rafaela A1 - Jung, Christian A1 - Alexopoulos, Spiros A1 - Atti, Vikrama Naga Babu A1 - Teixeira Boura, Cristiano José A1 - Herrmann, Ulf T1 - Operational experience and behaviour of a parabolic trough collector system with concrete thermal energy storage for process steam generation in Cyprus T2 - AIP Conference Proceedings N2 - As part of the transnational research project EDITOR, a parabolic trough collector system (PTC) with concrete thermal energy storage (C-TES) was installed and commissioned in Limassol, Cyprus. The system is located on the premises of the beverage manufacturer KEAN Soft Drinks Ltd. and its function is to supply process steam for the factory's pasteurisation process [1]. Depending on the factory's seasonally varying capacity for beverage production, the solar system delivers between 5 and 25 % of the total steam demand. In combination with the C-TES, the solar plant can supply process steam on demand before sunrise or after sunset. Furthermore, the C-TES compensates the PTC during the day in fluctuating weather conditions. The parabolic trough collector as well as the control and oil handling unit is designed and manufactured by Protarget AG, Germany. The C-TES is designed and produced by CADE Soluciones de Ingeniería, S.L., Spain. In the focus of this paper is the description of the operational experience with the PTC, C-TES and boiler during the commissioning and operation phase. Additionally, innovative optimisation measures are presented. Y1 - 2020 U6 - https://doi.org/10.1063/5.0029278 N1 - SOLARPACES 2019: International Conference on Concentrating Solar Power and Chemical Energy Systems, 1–4 October 2019, Daegu, South Korea IS - 2303 SP - 140004-1 EP - 140004-10 ER - TY - CHAP A1 - Schmidts, Oliver A1 - Kraft, Bodo A1 - Winkens, Marvin A1 - Zündorf, Albert T1 - Catalog integration of low-quality product data by attribute label ranking T2 - Proceedings of the 9th International Conference on Data Science, Technology and Applications DATA - Volume 1 N2 - The integration of product data from heterogeneous sources and manufacturers into a single catalog is often still a laborious, manual task. Especially small- and medium-sized enterprises face the challenge of timely integrating the data their business relies on to have an up-to-date product catalog, due to format specifications, low quality of data and the requirement of expert knowledge. Additionally, modern approaches to simplify catalog integration demand experience in machine learning, word vectorization, or semantic similarity that such enterprises do not have. Furthermore, most approaches struggle with low-quality data. We propose Attribute Label Ranking (ALR), an easy to understand and simple to adapt learning approach. ALR leverages a model trained on real-world integration data to identify the best possible schema mapping of previously unknown, proprietary, tabular format into a standardized catalog schema. Our approach predicts multiple labels for every attribute of an inpu t column. The whole column is taken into consideration to rank among these labels. We evaluate ALR regarding the correctness of predictions and compare the results on real-world data to state-of-the-art approaches. Additionally, we report findings during experiments and limitations of our approach. Y1 - 2020 SN - 978-989-758-440-4 U6 - https://doi.org/10.5220/0009831000900101 N1 - 9th International Conference on Data Science, Technologies and Applications (DATA 2020), 7 - 9 July 2020, online SP - 90 EP - 101 PB - SciTePress CY - Setúbal, Portugal ER - TY - CHAP A1 - Sildatke, Michael A1 - Karwanni, Hendrik A1 - Kraft, Bodo A1 - Schmidts, Oliver A1 - Zündorf, Albert T1 - Automated Software Quality Monitoring in Research Collaboration Projects T2 - ICSEW'20: Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops N2 - 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. Y1 - 2020 U6 - https://doi.org/10.1145/3387940.3391478 N1 - ICSE '20: 42nd International Conference on Software Engineering, Seoul, Republic of Korea, 27 June 2020 - 19 July 2020 SP - 603 EP - 610 PB - IEEE CY - New York, NY ER - TY - CHAP A1 - Tamaldin, Noreffendy A1 - Esch, Thomas A1 - Tonoli, Andrea A1 - Reisinger, Karl Heinz A1 - Sprenger, Hanna A1 - Razuli, Hisham T1 - ERASMUS+ United CBHE Automotive International Collaboration from European to South East Asia T2 - Proceedings of the 2nd African International Conference on Industrial Engineering and Operations Management N2 - 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. KW - European Framework and South East Asia KW - Technology Transfer KW - Capacity Building Higher Education KW - Malaysian Automotive Industry Y1 - 2020 SN - 978-1-7923-6123-4 SN - 2169-8767 N1 - 2nd African International Conference on Industrial Engineering and Operations Management; Harare, Zimbabwe, December 7-10, 2020 SP - 2970 EP - 2972 PB - IEOM Society International CY - Southfield ER - TY - CHAP A1 - Thoma, Andreas A1 - Fisher, Alex A1 - Bertrand, Olivier A1 - Braun, Carsten ED - Vouloutsi, Vasiliki ED - Mura, Anna ED - Tauber, Falk ED - Speck, Thomas ED - Prescott, Tony J. ED - Verschure, Paul F. M. J. T1 - Evaluation of possible flight strategies for close object evasion from bumblebee experiments T2 - Living Machines 2020: Biomimetic and Biohybrid Systems KW - Obstacle avoidance KW - Bumblebees KW - Flight control KW - UAV KW - MAV Y1 - 2020 SN - 978-3-030-64312-6 U6 - https://doi.org/10.1007/978-3-030-64313-3_34 N1 - 9th International Conference, Living Machines 2020, Freiburg, Germany, July 28–30, 2020, Proceedings SP - 354 EP - 365 PB - Springer CY - Cham ER -