This file was created by the TYPO3 extension bib --- Timezone: CEST Creation date: 2024-05-06 Creation time: 08-33-22 --- Number of references 7 inproceedings 2023_matzutt_street_problems 2023 11 27 3591-3593 Municipalities increasingly depend on citizens to file digital reports about issues such as potholes or illegal trash dumps to improve their response time. However, the responsible authorities may be incentivized to ignore certain reports, e.g., when addressing them inflicts high costs. In this work, we explore the applicability of blockchain technology to hold authorities accountable regarding filed reports. Our initial assessment indicates that our approach can be extended to benefit citizens and authorities in the future. street problems; accountability; consortium blockchain; privacy https://www.comsys.rwth-aachen.de/fileadmin/papers/2023/2023-matzutt-street-problems.pdf ACM Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security (CCS ’23), November 26-30, 2023, Copenhagen, Denmark Copenhagen, Denmark November 26-30, 2023 979-8-4007-0050-7/23/11 10.1145/3576915.3624367 1 RomanMatzutt JanPennekamp KlausWehrle inproceedings 2023-redefine-mpc-cosimulation Proceedings of the 14th IEEE International Conference on Smart Grid Communications (SmartGridComm 2023) 2023 10 redefine IEEE Proceedings of the 14th IEEE International Conference on Smart Grid Communications (SmartGridComm 2023) accepted 1 TobiasHeins RenéGlebke MirkoStoffers SriramGurumurthy JanHeesemann MartinaJosevski AntonelloMonti KlausWehrle inproceedings 2023_bodenbenner_fairsensor 2023 7 20 The long-term utility and reusability of measurement data from production processes depend on the appropriate contextualization of the measured values. These requirements further mandate that modifications to the context need to be recorded. To be (re-)used at all, the data must be easily findable in the first place, which requires arbitrary filtering and searching routines. Following the FAIR guiding principles, fostering findable, accessible, interoperable and reusable (FAIR) data, in this paper, the FAIR Sensor Ecosystem is proposed, which provides a contextualization middleware based on a unified data metamodel. All information and relations which might change over time are versioned and associated with temporal validity intervals to enable full reconstruction of a system's state at any point in time. A technical validation demonstrates the correctness of the FAIR Sensor Ecosystem, including its contextualization model and filtering techniques. State-of-the-art FAIRness assessment frameworks rate the proposed FAIR Sensor Ecosystem with an average FAIRness of 71%. The obtained rating can be considered remarkable, as deductions mainly result from the lack of fully appropriate FAIRness metrics and the absence of relevant community standards for the domain of the manufacturing industry. FAIR Data; Cyber-Physical Systems; Data Management; Data Contextualization; Internet of Production internet-of-production https://www.comsys.rwth-aachen.de/fileadmin/papers/2023/2023-bodenbenner-fair-ecosystem.pdf IEEE Proceedings of the 21th IEEE International Conference on Industrial Informatics (INDIN '23), July 17-20, 2023, Lemgo, Germany Lemgo, Germany July 17-20, 2023 978-1-6654-9313-0 2378-363X 10.1109/INDIN51400.2023.10218149 1 MatthiasBodenbenner JanPennekamp BenjaminMontavon KlausWehrle Robert H.Schmitt article Jakobs_2023_3 European Intellectual Property Review 2023 7 45 7 371-375 It has long been recognized in Europe and elsewhere that standards-development organizations (SDOs) may adopt policies that require their participants to license patents essential to the SDO’s standards (standards-essential patents or SEPs) to manufacturers of standardized products (“implementers”) on a royalty-free (RF) basis. This requirement contrasts with SDO policies that permit SEP holders to charge implementers monetary patent royalties, sometimes on terms that are specified as “fair, reasonable and nondiscriminatory” (FRAND). As demonstrated by two decades of intensive litigation around the world, FRAND royalties have given rise to intractable disputes regarding the manner in which such royalties should be calculated and adjudicated. In contrast, standards distributed on an RF basis are comparatively free from litigation and the attendant transaction costs. Accordingly, numerous SDOs around the world have adopted RF licensing policies and many widely adopted standards, including Bluetooth, USB, IPv6, HTTP, HTML and XML, are distributed on an RF basis. This note briefly discusses the commercial considerations surrounding RF standards, the relationship between RF standards and open source software (OSS) and the SDO policy mechanisms – including “universal reciprocity” -- that enable RF licensing to succeed in the marketplace. 0142-0461 10.2139/ssrn.4235647 1 JorgeContreras RudiBekkers BradBiddle EnricoBonadio Michael A.Carrier BernardChao CharlesDuan RichardGilbert JoachimHenkel ErikHovenkamp MartinHusovec KaiJakobs Dong-hyuKim Mark A.Lemley Brian J.Love LukeMcDonagh Fiona M.Scott Morton JasonSchultz TimothySimcoe Jennifer M.Urban Joy YXiang incollection 2023_rueppel_crd-b2.ii 2023 2 8 221-246 The main objectives in production technology are quality assurance, cost reduction, and guaranteed process safety and stability. Digital shadows enable a more comprehensive understanding and monitoring of processes on shop floor level. Thus, process information becomes available between decision levels, and the aforementioned criteria regarding quality, cost, or safety can be included in control decisions for production processes. The contextual data for digital shadows typically arises from heterogeneous sources. At shop floor level, the proximity to the process requires usage of available data as well as domain knowledge. Data sources need to be selected, synchronized, and processed. Especially high-frequency data requires algorithms for intelligent distribution and efficient filtering of the main information using real-time devices and in-network computing. Real-time data is enriched by simulations, metadata from product planning, and information across the whole process chain. Well-established analytical and empirical models serve as the base for new hybrid, gray box approaches. These models are then applied to optimize production process control by maximizing the productivity under given quality and safety constraints. To store and reuse the developed models, ontologies are developed and a data lake infrastructure is utilized and constantly enlarged laying the basis for a World Wide Lab (WWL). Finally, closing the control loop requires efficient quality assessment, immediately after the process and directly on the machine. This chapter addresses works in a connected job shop to acquire data, identify and optimize models, and automate systems and their deployment in the Internet of Production (IoP). Process control; Model-based control; Data aggregation; Model identification; Model optimization internet-of-production https://www.comsys.rwth-aachen.de/fileadmin/papers/2023/2023-rueppel-iop-b2.i.pdf Springer Interdisciplinary Excellence Accelerator Series Internet of Production: Fundamentals, Applications and Proceedings 978-3-031-44496-8 10.1007/978-3-031-44497-5_7 1 Adrian KarlRüppel MuzafferAy BenediktBiernat IkeKunze MarkusLandwehr SamuelMann JanPennekamp PascalRabe Mark P.Sanders DominikScheurenberg SvenSchiller TiandongXi DirkAbel ThomasBergs ChristianBrecher UweReisgen Robert H.Schmitt KlausWehrle incollection 2023_pennekamp_crd-a.i 2023 2 8 35-60 The Internet of Production (IoP) leverages concepts such as digital shadows, data lakes, and a World Wide Lab (WWL) to advance today’s production. Consequently, it requires a technical infrastructure that can support the agile deployment of these concepts and corresponding high-level applications, which, e.g., demand the processing of massive data in motion and at rest. As such, key research aspects are the support for low-latency control loops, concepts on scalable data stream processing, deployable information security, and semantically rich and efficient long-term storage. In particular, such an infrastructure cannot continue to be limited to machines and sensors, but additionally needs to encompass networked environments: production cells, edge computing, and location-independent cloud infrastructures. Finally, in light of the envisioned WWL, i.e., the interconnection of production sites, the technical infrastructure must be advanced to support secure and privacy-preserving industrial collaboration. To evolve today’s production sites and lay the infrastructural foundation for the IoP, we identify five broad streams of research: (1) adapting data and stream processing to heterogeneous data from distributed sources, (2) ensuring data interoperability between systems and production sites, (3) exchanging and sharing data with different stakeholders, (4) network security approaches addressing the risks of increasing interconnectivity, and (5) security architectures to enable secure and privacy-preserving industrial collaboration. With our research, we evolve the underlying infrastructure from isolated, sparsely networked production sites toward an architecture that supports high-level applications and sophisticated digital shadows while facilitating the transition toward a WWL. Cyber-physical production systems; Data streams; Industrial data processing; Industrial network security; Industrial data security; Secure industrial collaboration internet-of-production https://www.comsys.rwth-aachen.de/fileadmin/papers/2023/2023-pennekamp-iop-a.i.pdf Springer Interdisciplinary Excellence Accelerator Series Internet of Production: Fundamentals, Applications and Proceedings 978-3-031-44496-8 10.1007/978-3-031-44497-5_2 1 JanPennekamp AnastasiiaBelova ThomasBergs MatthiasBodenbenner AndreasBührig-Polaczek MarkusDahlmanns IkeKunze MoritzKröger SandraGeisler MartinHenze DanielLütticke BenjaminMontavon PhilippNiemietz LuciaOrtjohann MaximilianRudack Robert H.Schmitt UweVroomen KlausWehrle MichaelZeng incollection 2023_klugewilkes_crd-b2.iv 2023 2 8 303-328 The increasing product variability and lack of skilled workers demand for autonomous, flexible production. Since assembly is considered a main cost driver and accounts for a major part of production time, research focuses on new technologies in assembly. The paradigm of Line-less Mobile Assembly Systems (LMAS) provides a solution for the future of assembly by mobilizing all resources. Thus, dynamic product routes through spatiotemporally configured assembly stations on a shop floor free of fixed obstacles are enabled. In this chapter, we present research focal points on different levels of LMAS, starting with the macroscopic level of formation planning, followed by the mesoscopic level of mobile robot control and multipurpose input devices and the microscopic level of services, such as interpreting autonomous decisions and in-network computing. We provide cross-level data and knowledge transfer through a novel ontology-based knowledge management. Overall, our work contributes to future safe and predictable human-robot collaboration in dynamic LMAS stations based on accurate online formation and motion planning of mobile robots, novel human-machine interfaces and networking technologies, as well as trustworthy AI-based decisions. Lineless mobile assembly systems (LMAS); Formation planning; Online motion planning; In-network computing; Interpretable AI; Human-machine collaboration; Ontology-based knowledge management internet-of-production https://www.comsys.rwth-aachen.de/fileadmin/papers/2023/2023-klugewilkes-iop-b2.iv.pdf Springer Interdisciplinary Excellence Accelerator Series Internet of Production: Fundamentals, Applications and Proceedings 978-3-031-44496-8 10.1007/978-3-031-44497-5_13 1 AlineKluge-Wilkes RalphBaier DanielGossen IkeKunze AleksandraMüller AmirShahidi DominikWolfschläger ChristianBrecher BurkhardCorves MathiasHüsing VerenaNitsch Robert H.Schmitt KlausWehrle