TY - CHAP A1 - Welden, Melanie A1 - Severins, Robin A1 - Poghossian, Arshak A1 - Wege, Christina A1 - Siegert, Petra A1 - Keusgen, Michael A1 - Schöning, Michael Josef T1 - Studying the immobilization of acetoin reductase with Tobacco mosaic virus particles on capacitive field-effect sensors T2 - 2022 IEEE International Symposium on Olfaction and Electronic Nose (ISOEN) N2 - A capacitive electrolyte-insulator-semiconductor (EISCAP) biosensor modified with Tobacco mosaic virus (TMV) particles for the detection of acetoin is presented. The enzyme acetoin reductase (AR) was immobilized on the surface of the EISCAP using TMV particles as nanoscaffolds. The study focused on the optimization of the TMV-assisted AR immobilization on the Ta 2 O 5 -gate EISCAP surface. The TMV-assisted acetoin EISCAPs were electrochemically characterized by means of leakage-current, capacitance-voltage, and constant-capacitance measurements. The TMV-modified transducer surface was studied via scanning electron microscopy. KW - Tobacco mosaic virus KW - acetoin KW - capacitive field-effect biosensor KW - enzyme immobilization Y1 - 2022 SN - 978-1-6654-5860-3 (Online) SN - 978-1-6654-5861-0 (Print) U6 - http://dx.doi.org/10.1109/ISOEN54820.2022.9789657 N1 - IEEE International Symposium on Olfaction and Electronic Nose (ISOEN), 29 May 2022 - 01 June 2022, Aveiro, Portugal. PB - IEEE ER - TY - CHAP A1 - Evans, Benjamin A1 - Braun, Sebastian A1 - Ulmer, Jessica A1 - Wollert, Jörg T1 - AAS implementations - current problems and solutions T2 - 20th International Conference on Mechatronics - Mechatronika (ME) N2 - The fourth industrial revolution presents a multitude of challenges for industries, one of which being the increased flexibility required of manufacturing lines as a result of increased consumer demand for individualised products. One solution to tackle this challenge is the digital twin, more specifically the standardised model of a digital twin also known as the asset administration shell. The standardisation of an industry wide communications tool is a critical step in enabling inter-company operations. This paper discusses the current state of asset administration shells, the frameworks used to host them and their problems that need to be addressed. To tackle these issues, we propose an event-based server capable of drastically reducing response times between assets and asset administration shells and a multi-agent system used for the orchestration and deployment of the shells in the field. KW - Industry 4.0 KW - Multi-agent Systems KW - Digital Twin KW - Asset Administration Shell Y1 - 2022 SN - 978-1-6654-1040-3 U6 - http://dx.doi.org/10.1109/ME54704.2022.9982933 PB - IEEE ER - TY - JOUR A1 - Coll-Perales, Baldomero A1 - Schulte-Tigges, Joschua A1 - Rondinone, Michele A1 - Gozalvez, Javier A1 - Reke, Michael A1 - Matheis, Dominik A1 - Walter, Thomas T1 - Prototyping and evaluation of infrastructure-assisted transition of control for cooperative automated vehicles JF - IEEE Transactions on Intelligent Transportation Systems N2 - Automated driving is now possible in diverse road and traffic conditions. However, there are still situations that automated vehicles cannot handle safely and efficiently. In this case, a Transition of Control (ToC) is necessary so that the driver takes control of the driving. Executing a ToC requires the driver to get full situation awareness of the driving environment. If the driver fails to get back the control in a limited time, a Minimum Risk Maneuver (MRM) is executed to bring the vehicle into a safe state (e.g., decelerating to full stop). The execution of ToCs requires some time and can cause traffic disruption and safety risks that increase if several vehicles execute ToCs/MRMs at similar times and in the same area. This study proposes to use novel C-ITS traffic management measures where the infrastructure exploits V2X communications to assist Connected and Automated Vehicles (CAVs) in the execution of ToCs. The infrastructure can suggest a spatial distribution of ToCs, and inform vehicles of the locations where they could execute a safe stop in case of MRM. This paper reports the first field operational tests that validate the feasibility and quantify the benefits of the proposed infrastructure-assisted ToC and MRM management. The paper also presents the CAV and roadside infrastructure prototypes implemented and used in the trials. The conducted field trials demonstrate that infrastructure-assisted traffic management solutions can reduce safety risks and traffic disruptions. KW - Automated driving KW - automated vehicles KW - connected automated vehicles KW - CAV KW - experimental evaluation Y1 - 2021 U6 - http://dx.doi.org/10.1109/TITS.2021.3061085 SN - 1524-9050 (Print) SN - 1558-0016 (Online) VL - 23 IS - 7 SP - 6720 EP - 6736 PB - IEEE ER - TY - JOUR A1 - Serror, Martin A1 - Hack, Sacha A1 - Henze, Martin A1 - Schuba, Marko A1 - Wehrle, Klaus T1 - Challenges and Opportunities in Securing the Industrial Internet of Things JF - IEEE Transactions on Industrial Informatics Y1 - 2021 U6 - http://dx.doi.org/10.1109/TII.2020.3023507 SN - 1941-0050 VL - 17 IS - 5 SP - 2985 EP - 2996 PB - IEEE CY - New York ER - TY - JOUR A1 - Braun, Sebastian A1 - Cheng, Chi-Tsun A1 - Dowey, Steve A1 - Wollert, Jörg T1 - Performance evaluation of skill-based order-assignment in production environments with multi-agent systems JF - IEEE Journal of Emerging and Selected Topics in Industrial Electronics N2 - The fourth industrial revolution introduces disruptive technologies to production environments. One of these technologies are multi-agent systems (MASs), where agents virtualize machines. However, the agent's actual performances in production environments can hardly be estimated as most research has been focusing on isolated projects and specific scenarios. We address this gap by implementing a highly connected and configurable reference model with quantifiable key performance indicators (KPIs) for production scheduling and routing in single-piece workflows. Furthermore, we propose an algorithm to optimize the search of extrema in highly connected distributed systems. The benefits, limits, and drawbacks of MASs and their performances are evaluated extensively by event-based simulations against the introduced model, which acts as a benchmark. Even though the performance of the proposed MAS is, on average, slightly lower than the reference system, the increased flexibility allows it to find new solutions and deliver improved factory-planning outcomes. Our MAS shows an emerging behavior by using flexible production techniques to correct errors and compensate for bottlenecks. This increased flexibility offers substantial improvement potential. The general model in this paper allows the transfer of the results to estimate real systems or other models. KW - cyber-physical production systems KW - event-based simulation KW - multi-agent systems KW - digital factory KW - industrial agents Y1 - 2021 U6 - http://dx.doi.org/10.1109/JESTIE.2021.3108524 SN - 2687-9735 IS - Early Access PB - IEEE CY - New York ER - TY - CHAP A1 - Eltester, Niklas Sebastian A1 - Ferrein, Alexander A1 - Schiffer, Stefan T1 - A smart factory setup based on the RoboCup logistics league T2 - 2020 IEEE Conference on Industrial Cyberphysical Systems (ICPS) N2 - 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. Y1 - 2020 U6 - http://dx.doi.org/10.1109/ICPS48405.2020.9274766 N1 - 2020 IEEE Conference on Industrial Cyberphysical Systems (ICPS), 10-12 June 2020, Tampere, Finland. SP - 297 EP - 302 PB - IEEE ER - TY - JOUR A1 - Khayyam, Hamid A1 - Jamali, Ali A1 - Bab-Hadiashar, Alireza A1 - Esch, Thomas A1 - Ramakrishna, Seeram A1 - Jalili, Mahdi A1 - Naebe, Minoo T1 - A Novel Hybrid Machine Learning Algorithm for Limited and Big Data Modeling with Application in Industry 4.0 JF - IEEE Access N2 - To meet the challenges of manufacturing smart products, the manufacturing plants have been radically changed to become smart factories underpinned by industry 4.0 technologies. The transformation is assisted by employment of machine learning techniques that can deal with modeling both big or limited data. This manuscript reviews these concepts and present a case study that demonstrates the use of a novel intelligent hybrid algorithms for Industry 4.0 applications with limited data. In particular, an intelligent algorithm is proposed for robust data modeling of nonlinear systems based on input-output data. In our approach, a novel hybrid data-driven combining the Group-Method of Data-Handling and Singular-Value Decomposition is adapted to find an offline deterministic model combined with Pareto multi-objective optimization to overcome the overfitting issue. An Unscented-Kalman-Filter is also incorporated to update the coefficient of the deterministic model and increase its robustness against data uncertainties. The effectiveness of the proposed method is examined on a set of real industrial measurements. Y1 - 2020 U6 - http://dx.doi.org/10.1109/ACCESS.2020.2999898 SN - 2169-3536 VL - 8 IS - Art. 9108222 SP - 111381 EP - 111393 PB - IEEE CY - New York, NY ER - TY - JOUR A1 - Khayyam, Hamid A1 - Jamali, Ali A1 - Bab-Hadiashar, Alireza A1 - Esch, Thomas A1 - Ramakrishna, Seeram A1 - Jalil, Mahdi A1 - Naebe, Minoo T1 - A Novel Hybrid Machine Learning Algorithm for Limited and Big Data Modelling with Application in Industry 4.0 JF - IEEE Access N2 - To meet the challenges of manufacturing smart products, the manufacturing plants have been radically changed to become smart factories underpinned by industry 4.0 technologies. The transformation is assisted by employment of machine learning techniques that can deal with modeling both big or limited data. This manuscript reviews these concepts and present a case study that demonstrates the use of a novel intelligent hybrid algorithms for Industry 4.0 applications with limited data. In particular, an intelligent algorithm is proposed for robust data modeling of nonlinear systems based on input-output data. In our approach, a novel hybrid data-driven combining the Group-Method of Data-Handling and Singular-Value Decomposition is adapted to find an offline deterministic model combined with Pareto multi-objective optimization to overcome the overfitting issue. An Unscented-Kalman-Filter is also incorporated to update the coefficient of the deterministic model and increase its robustness against data uncertainties. The effectiveness of the proposed method is examined on a set of real industrial measurements. Y1 - 2020 SN - 2169-3536 U6 - http://dx.doi.org/10.1109/ACCESS.2020.2999898 SP - 1 EP - 12 PB - IEEE CY - New York, NY ER - TY - JOUR A1 - Fiedler, Thomas M. A1 - Ladd, Mark E. A1 - Clemens, Markus A1 - Bitz, Andreas T1 - Safety of subjects during radiofrequency exposure in ultra-high-field magnetic resonance imaging JF - IEEE Letters on Electromagnetic Compatibility Practice and Applications N2 - Magnetic resonance imaging (MRI) is one of the most important medical imaging techniques. Since the introduction of MRI in the mid-1980s, there has been a continuous trend toward higher static magnetic fields to obtain i.a. a higher signal-to-noise ratio. The step toward ultra-high-field (UHF) MRI at 7 Tesla and higher, however, creates several challenges regarding the homogeneity of the spin excitation RF transmit field and the RF exposure of the subject. In UHF MRI systems, the wavelength of the RF field is in the range of the diameter of the human body, which can result in inhomogeneous spin excitation and local SAR hotspots. To optimize the homogeneity in a region of interest, UHF MRI systems use parallel transmit systems with multiple transmit antennas and time-dependent modulation of the RF signal in the individual transmit channels. Furthermore, SAR increases with increasing field strength, while the SAR limits remain unchanged. Two different approaches to generate the RF transmit field in UHF systems using antenna arrays close and remote to the body are investigated in this letter. Achievable imaging performance is evaluated compared to typical clinical RF transmit systems at lower field strength. The evaluation has been performed under consideration of RF exposure based on local SAR and tissue temperature. Furthermore, results for thermal dose as an alternative RF exposure metric are presented. Y1 - 2020 SN - 2637-6423 U6 - http://dx.doi.org/10.1109/LEMCPA.2020.3029747 VL - 2 IS - 3 SP - 1 EP - 8 PB - IEEE CY - New York, NY ER - TY - JOUR A1 - Hüning, Felix A1 - Backes, Andreas T1 - Direct observation of large Barkhausen jump in thin Vicalloy wires JF - IEEE Magnetics Letters Y1 - 2020 SN - 1949-307X U6 - http://dx.doi.org/10.1109/LMAG.2020.3046411 VL - 11 IS - Art. 2506504 SP - 1 EP - 4 PB - IEEE CY - New York, NY ER -