This file was created by the TYPO3 extension bib --- Timezone: CEST Creation date: 2024-10-16 Creation time: 04-12-50 --- Number of references 8 inproceedings 2021-kunze-signal-detection 2021 6 10 internet-of-production https://www.comsys.rwth-aachen.de/fileadmin/papers/2021/2021-kunze-signal-detection.pdf IEEE Proceedings of the 2021 IEEE 30th International Symposium on Industrial Electronics (ISIE) 978-1-7281-9023-5 2163-5145 10.1109/ISIE45552.2021.9576221 1 IkeKunze PhilippNiemietz LiamTirpitz RenéGlebke DanielTrauth ThomasBergs KlausWehrle article 2020_niemietz_stamping Procedia Manufacturing 2020 7 11 49 61-68 Sharing data between companies throughout the supply chain is expected to be beneficial for product quality as well as for the economical savings in the manufacturing industry. To utilize the available data in the vision of an Internet of Production (IoP) a precise condition monitoring of manufacturing and production processes that facilitates the quantification of influences throughout the supply chain is inevitable. In this paper, we consider stamping processes in the context of an Internet of Production and the preliminaries for analytical models that utilize the ever-increasing available data. Three research objectives to cope with the amount of data and for a methodology to monitor, analyze and evaluate the influence of available data onto stamping processes have been identified: (i) State detection based on cyclic sensor signals, (ii) mapping of in- and output parameter variations onto process states, and (iii) models for edge and in-network computing approaches. After discussing state-of-the-art approaches to monitor stamping processes and the introduction of the fineblanking process as an exemplary stamping process, a research roadmap for an IoP enabling modeling framework is presented. Proceedings of the 8th International Conference on Through-Life Engineering Service (TESConf '19), October 27-29, 2019, Cleveland, OH, USA Stamping Process; Industry 4.0; Fine-blanking; Internet of production; Condition monitoring; Data analytics internet-of-production https://www.comsys.rwth-aachen.de/fileadmin/papers/2020/2020-niemietz-stamping-modelling.pdf Elsevier Cleveland, OH, USA October 27-29, 2019 2351-9789 10.1016/j.promfg.2020.06.012 1 PhilippNiemietz JanPennekamp IkeKunze DanielTrauth KlausWehrle ThomasBergs inproceedings 2020_pennekamp_supply_chain_accountability 2020 6 7 Today's supply chains are becoming increasingly flexible in nature. While adaptability is vastly increased, these more dynamic associations necessitate more extensive data sharing among different stakeholders while simultaneously overturning previously established levels of trust. Hence, manufacturers' demand to track goods and to investigate root causes of issues across their supply chains becomes more challenging to satisfy within these now untrusted environments. Complementarily, suppliers need to keep any data irrelevant to such routine checks secret to remain competitive. To bridge the needs of contractors and suppliers in increasingly flexible supply chains, we thus propose to establish a privacy-preserving and distributed multi-hop accountability log among the involved stakeholders based on Attribute-based Encryption and backed by a blockchain. Our large-scale feasibility study is motivated by a real-world manufacturing process, i.e., a fine blanking line, and reveals only modest costs for multi-hop tracing and tracking of goods. supply chain; multi-hop tracking and tracing; blockchain; attribute-based encryption; Internet of Production internet-of-production https://comsys.rwth-aachen.de/fileadmin/papers/2020/2020-pennekamp-supply-chain-privacy.pdf IEEE Proceedings of the 2020 IEEE International Conference on Communications Workshops (ICC Workshops '20), 1st Workshop on Blockchain for IoT and Cyber-Physical Systems (BIoTCPS '20), June 7-11, 2020, Dublin, Ireland Dublin, Ireland June 7-11, 2020 978-1-7281-7440-2 2474-9133 10.1109/ICCWorkshops49005.2020.9145100 1 JanPennekamp LennartBader RomanMatzutt PhilippNiemietz DanielTrauth MartinHenze ThomasBergs KlausWehrle article 2020_gleim_factDAG IEEE Internet of Things Journal 2020 4 14 7 4 3243-3253 In the production industry, the volume, variety and velocity of data as well as the number of deployed protocols increase exponentially due to the influences of IoT advances. While hundreds of isolated solutions exist to utilize this data, e.g., optimizing processes or monitoring machine conditions, the lack of a unified data handling and exchange mechanism hinders the implementation of approaches to improve the quality of decisions and processes in such an interconnected environment. The vision of an Internet of Production promises the establishment of a Worldwide Lab, where data from every process in the network can be utilized, even interorganizational and across domains. While numerous existing approaches consider interoperability from an interface and communication system perspective, fundamental questions of data and information interoperability remain insufficiently addressed. In this paper, we identify ten key issues, derived from three distinctive real-world use cases, that hinder large-scale data interoperability for industrial processes. Based on these issues we derive a set of five key requirements for future (IoT) data layers, building upon the FAIR data principles. We propose to address them by creating FactDAG, a conceptual data layer model for maintaining a provenance-based, directed acyclic graph of facts, inspired by successful distributed version-control and collaboration systems. Eventually, such a standardization should greatly shape the future of interoperability in an interconnected production industry. Data Management; Data Versioning; Interoperability; Industrial Internet of Things; Worldwide Lab internet-of-production https://comsys.rwth-aachen.de/fileadmin/papers/2020/2020-gleim-iotj-iop-interoperability.pdf IEEE 2327-4662 10.1109/JIOT.2020.2966402 1 LarsGleim JanPennekamp MartinLiebenberg MelanieBuchsbaum PhilippNiemietz SimonKnape AlexanderEpple SimonStorms DanielTrauth ThomasBergs ChristianBrecher StefanDecker GerhardLakemeyer KlausWehrle article 2019-unterberg-matclass Production Engineering 2019 11 13 13 6 743-749 internet-of-production 10.1007/s11740-019-00928-w 1 MartinUnterberg PhillipNiemietz DanielTrauth KlausWehrle ThomasBergs inproceedings 2019_pennekamp_dataflows 2019 11 11 27-38 The Internet of Production (IoP) envisions the interconnection of previously isolated CPS in the area of manufacturing across institutional boundaries to realize benefits such as increased profit margins and product quality as well as reduced product development costs and time to market. This interconnection of CPS will lead to a plethora of new dataflows, especially between (partially) distrusting entities. In this paper, we identify and illustrate these envisioned inter-organizational dataflows and the participating entities alongside two real-world use cases from the production domain: a fine blanking line and a connected job shop. Our analysis allows us to identify distinct security and privacy demands and challenges for these new dataflows. As a foundation to address the resulting requirements, we provide a survey of promising technical building blocks to secure inter-organizational dataflows in an IoP and propose next steps for future research. Consequently, we move an important step forward to overcome security and privacy concerns as an obstacle for realizing the promised potentials in an Internet of Production. Internet of Production; dataflows; Information Security internet-of-production https://www.comsys.rwth-aachen.de/fileadmin/papers/2019/2019-pennekamp-dataflows.pdf ACM Proceedings of the 5th ACM Workshop on Cyber-Physical Systems Security and PrivaCy (CPS-SPC '19), co-located with the 26th ACM SIGSAC Conference on Computer and Communications Security (CCS '19), November 11-15, 2019, London, United Kingdom London, United Kingdom November 11-15, 2019 978-1-4503-6831-5/19/11 10.1145/3338499.3357357 1 JanPennekamp MartinHenze SimoSchmidt PhilippNiemietz MarcelFey DanielTrauth ThomasBergs ChristianBrecher KlausWehrle inproceedings 2019_pennekamp_infrastructure 2019 5 8 31-37 New levels of cross-domain collaboration between manufacturing companies throughout the supply chain are anticipated to bring benefits to both suppliers and consumers of products. Enabling a fine-grained sharing and analysis of data among different stakeholders in an automated manner, such a vision of an Internet of Production (IoP) introduces demanding challenges to the communication, storage, and computation infrastructure in production environments. In this work, we present three example cases that would benefit from an IoP (a fine blanking line, a high pressure die casting process, and a connected job shop) and derive requirements that cannot be met by today’s infrastructure. In particular, we identify three orthogonal research objectives: (i) real-time control of tightly integrated production processes to offer seamless low-latency analysis and execution, (ii) storing and processing heterogeneous production data to support scalable data stream processing and storage, and (iii) secure privacy-aware collaboration in production to provide a basis for secure industrial collaboration. Based on a discussion of state-of-the-art approaches for these three objectives, we create a blueprint for an infrastructure acting as an enabler for an IoP. Internet of Production; Cyber-Physical Systems; Data Processing; Low Latency; Secure Industrial Collaboration internet-of-production https://www.comsys.rwth-aachen.de/fileadmin/papers/2019/2019-pennekamp-iop-infrastructure.pdf IEEE Proceedings of the 2nd IEEE International Conference on Industrial Cyber-Physical Systems (ICPS '19), May 6-9, 2019, Taipei, TW Taipei, TW May 6-9, 2019 978-1-5386-8500-6/19 10.1109/ICPHYS.2019.8780276 1 JanPennekamp RenéGlebke MartinHenze TobiasMeisen ChristophQuix RihanHai LarsGleim PhilippNiemietz MaximilianRudack SimonKnape AlexanderEpple DanielTrauth UweVroomen ThomasBergs ChristianBrecher AndreasBührig-Polaczek MatthiasJarke KlausWehrle inproceedings 2019-glebke-hicss-integrated 2019 1 8 7252-7261 internet-of-production,reflexes https://www.comsys.rwth-aachen.de/fileadmin/papers/2019/2019-glebke-integrated.pdf Online University of Hawai'i at Manoa / AIS Proceedings of the 52nd Hawaii International Conference on System Sciences (HICSS), Wailea, HI, USA en 978-0-9981331-2-6 10.24251/HICSS.2019.871 1 RenéGlebke MartinHenze KlausWehrle PhilippNiemietz DanielTrauth PatrickMattfeld ThomasBergs