This file was created by the TYPO3 extension bib --- Timezone: CEST Creation date: 2024-07-04 Creation time: 16-18-42 --- Number of references 9 article 2023_pennekamp_purchase_inquiries ACM Transactions on Internet Technology 2023 11 17 23 4 Dynamic and flexible business relationships are expected to become more important in the future to accommodate specialized change requests or small-batch production. Today, buyers and sellers must disclose sensitive information on products upfront before the actual manufacturing. However, without a trust relation, this situation is precarious for the involved companies as they fear for their competitiveness. Related work overlooks this issue so far: Existing approaches only protect the information of a single party only, hindering dynamic and on-demand business relationships. To account for the corresponding research gap of inadequately privacy-protected information and to deal with companies without an established trust relation, we pursue the direction of innovative privacy-preserving purchase inquiries that seamlessly integrate into today's established supplier management and procurement processes. Utilizing well-established building blocks from private computing, such as private set intersection and homomorphic encryption, we propose two designs with slightly different privacy and performance implications to securely realize purchase inquiries over the Internet. In particular, we allow buyers to consider more potential sellers without sharing sensitive information and relieve sellers of the burden of repeatedly preparing elaborate yet discarded offers. We demonstrate our approaches' scalability using two real-world use cases from the domain of production technology. Overall, we present deployable designs that offer two-way privacy for purchase inquiries and, in turn, fill a gap that currently hinders establishing dynamic and flexible business relationships. In the future, we expect significantly increasing research activity in this overlooked area to address the needs of an evolving production landscape. bootstrapping procurement; secure industrial collaboration; private set intersection; homomorphic encryption; Internet of Production internet-of-production https://www.comsys.rwth-aachen.de/fileadmin/papers/2023/2023-pennekamp-purchase-inquiries.pdf ACM 1533-5399 10.1145/3599968 1 JanPennekamp MarkusDahlmanns FrederikFuhrmann TimoHeutmann AlexanderKreppein DennisGrunert ChristophLange Robert H.Schmitt 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 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_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_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 inproceedings 2021_kiesel_5g 2021 12 15 739-744 Latency-critical applications in production promise to be essential enablers for performance improvement in production. However, they require the right and often wireless communication system. 5G technology appears to be an effective way to achieve communication system for these applications. Its estimated economic benefit on production gross domestic product is immense ($740 billion Euro until 2030). However, 55% of production companies state that 5G technology deployment is currently not a subject matter for them and mainly state the lack of knowledge on benefits as a reason. Currently, it is missing an approach or model for a use case specific, data-based evaluation of 5G technology influence on the performance of production applications. Therefore, this paper presents a model to evaluate the potential of 5G technology for latency-critical applications in production. First, we derive requirements for the model to fulfill the decision-makers' needs. Second, we analyze existing evaluation approaches regarding their fulfillment of the derived requirements. Third, based on outlined research gaps, we develop a model fulfilling the requirements. Fourth, we give an outlook for further research needs. 5G technology; latency-critical applications; production; evaluation model https://www.comsys.rwth-aachen.de/fileadmin/papers/2021/2021-kiesel-5g-model.pdf IEEE Proceedings of the 28th IEEE International Conference on Industrial Engineering and Engineering Management (IEEM '21), December 13-16, 2021, Singapore, Singapore Singapore, Singapore December 13-16, 2021 978-1-6654-3771-4 10.1109/IEEM50564.2021.9673074 1 RaphaelKiesel FalkBoehm JanPennekamp Robert H.Schmitt inproceedings 2021_pennekamp_bootstrapping 2021 11 15 RWTH-2021-09499 In addition to quality improvements and cost reductions, dynamic and flexible business relationships are expected to become more important in the future to account for specific customer change requests or small-batch production. Today, despite reservation, sensitive information must be shared upfront between buyers and sellers. However, without a trust relation, this situation is precarious for the involved companies as they fear for their competitiveness following information leaks or breaches of their privacy. To address this issue, the concepts of confidential computing and cloud computing come to mind as they promise to offer scalable approaches that preserve the privacy of participating companies. In particular, designs building on confidential computing can help to technically enforce privacy. Moreover, cloud computing constitutes an elegant design choice to scale these novel protocols to industry needs while limiting the setup and management overhead for practitioners. Thus, novel approaches in this area can advance the status quo of bootstrapping new relationships as they provide privacy-preserving alternatives that are suitable for immediate deployment. bootstrapping procurement; business relationships; secure industrial collaboration; privacy; Internet of Production internet-of-production https://www.comsys.rwth-aachen.de/fileadmin/papers/2021/2021-pennekamp-bootstrapping.pdf RWTH Aachen University Blitz Talk at the 2021 Cloud Computing Security Workshop (CCSW '21), co-located with the 28th ACM SIGSAC Conference on Computer and Communications Security (CCS '21), November 15-19, 2021, Seoul, Korea RWTH Aachen University Seoul, Korea November 14, 2021 10.18154/RWTH-2021-09499 JanPennekamp FrederikFuhrmann MarkusDahlmanns TimoHeutmann AlexanderKreppein DennisGrunert ChristophLange Robert H.Schmitt KlausWehrle inproceedings 2021-kunze-coordinate-transformation 2021 5 11 334-340 in-network computing; latency; approximation internet-of-production,reflexes https://www.comsys.rwth-aachen.de/fileadmin/papers/2021/2021-kunze-coordinate-transformation.pdf IEEE Proceedings of the 4th IEEE International Conference on Industrial Cyber-Physical Systems (ICPS '21) 978-1-7281-6207-2 10.1109/ICPS49255.2021.9468247 1 IkeKunze RenéGlebke JanScheiper MatthiasBodenbenner Robert H.Schmitt KlausWehrle article 2021_buckhorst_lmas Procedia CIRP 2021 5 3 99 448-453 Assembly systems must provide maximum flexibility qualified by organization and technology to offer cost-compliant performance features to differentiate themselves from competitors in buyers' markets. By mobilization of multipurpose resources and dynamic planning, Line-less Mobile Assembly Systems (LMASs) offer organizational reconfigurability. By proposing a holarchy to combine LMASs with the concept of an Internet of Production (IoP), we enable LMASs to source valuable information from cross-level production networks, physical resources, software nodes, and data stores that are interconnected in an IoP. The presented holarchy provides a concept of how to address future challenges, meet the requirements of shorter lead times, and unique lifecycle support. The paper suggests an application of decision making, distributed sensor services, recommender-based data reduction, and in-network computing while considering safety and human usability alike. Proceedings of the 14th CIRP Conference on Intelligent Computation in Manufacturing Engineering (ICME '20), July 14-17, 2020, Gulf of Naples, Italy Internet of Production; Line-less Mobile Assembly System; Industrial Assembly; Smart Factory internet-of-production https://www.comsys.rwth-aachen.de/fileadmin/papers/2021/2021-buckhorst-holarchy.pdf Elsevier Gulf of Naples, Italy July 14-17, 2020 2212-8271 10.1016/j.procir.2021.03.064 1 Armin F.Buckhorst BenjaminMontavon DominikWolfschläger MelanieBuchsbaum AmirShahidi HenningPetruck IkeKunze JanPennekamp ChristianBrecher MathiasHüsing BurkhardCorves VerenaNitsch KlausWehrle Robert H.Schmitt