% % This file was created by the TYPO3 extension % bib % --- Timezone: CEST % Creation date: 2024-04-18 % Creation time: 11-36-27 % --- Number of references % 9 % @Incollection { 2023_pennekamp_crd-a.i, title = {Evolving the Digital Industrial Infrastructure for Production: Steps Taken and the Road Ahead}, year = {2023}, month = {2}, day = {8}, pages = {35-60}, abstract = {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.}, keywords = {Cyber-physical production systems; Data streams; Industrial data processing; Industrial network security; Industrial data security; Secure industrial collaboration}, tags = {internet-of-production}, url = {https://www.comsys.rwth-aachen.de/fileadmin/papers/2023/2023-pennekamp-iop-a.i.pdf}, publisher = {Springer}, series = {Interdisciplinary Excellence Accelerator Series}, booktitle = {Internet of Production: Fundamentals, Applications and Proceedings}, ISBN = {978-3-031-44496-8}, DOI = {10.1007/978-3-031-44497-5_2}, reviewed = {1}, author = {Pennekamp, Jan and Belova, Anastasiia and Bergs, Thomas and Bodenbenner, Matthias and B{\"u}hrig-Polaczek, Andreas and Dahlmanns, Markus and Kunze, Ike and Kr{\"o}ger, Moritz and Geisler, Sandra and Henze, Martin and L{\"u}tticke, Daniel and Montavon, Benjamin and Niemietz, Philipp and Ortjohann, Lucia and Rudack, Maximilian and Schmitt, Robert H. and Vroomen, Uwe and Wehrle, Klaus and Zeng, Michael} } @Inproceedings { 2021-kunze-signal-detection, title = {Detecting Out-Of-Control Sensor Signals in Sheet Metal Forming using In-Network Computing}, year = {2021}, month = {6}, day = {10}, tags = {internet-of-production}, url = {https://www.comsys.rwth-aachen.de/fileadmin/papers/2021/2021-kunze-signal-detection.pdf}, publisher = {IEEE}, booktitle = {Proceedings of the 2021 IEEE 30th International Symposium on Industrial Electronics (ISIE)}, ISBN = {978-1-7281-9023-5}, ISSN = {2163-5145}, DOI = {10.1109/ISIE45552.2021.9576221}, reviewed = {1}, author = {Kunze, Ike and Niemietz, Philipp and Tirpitz, Liam and Glebke, Ren{\'e} and Trauth, Daniel and Bergs, Thomas and Wehrle, Klaus} } @Article { 2020_niemietz_stamping, title = {Stamping Process Modelling in an Internet of Production}, journal = {Procedia Manufacturing}, year = {2020}, month = {7}, day = {11}, volume = {49}, pages = {61-68}, abstract = {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.}, note = {Proceedings of the 8th International Conference on Through-Life Engineering Service (TESConf '19), October 27-29, 2019, Cleveland, OH, USA}, keywords = {Stamping Process; Industry 4.0; Fine-blanking; Internet of production; Condition monitoring; Data analytics}, tags = {internet-of-production}, url = {https://www.comsys.rwth-aachen.de/fileadmin/papers/2020/2020-niemietz-stamping-modelling.pdf}, publisher = {Elsevier}, event_place = {Cleveland, OH, USA}, event_date = {October 27-29, 2019}, ISSN = {2351-9789}, DOI = {10.1016/j.promfg.2020.06.012}, reviewed = {1}, author = {Niemietz, Philipp and Pennekamp, Jan and Kunze, Ike and Trauth, Daniel and Wehrle, Klaus and Bergs, Thomas} } @Inproceedings { 2020_pennekamp_supply_chain_accountability, title = {Private Multi-Hop Accountability for Supply Chains}, year = {2020}, month = {6}, day = {7}, abstract = {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.}, keywords = {supply chain; multi-hop tracking and tracing; blockchain; attribute-based encryption; Internet of Production}, tags = {internet-of-production}, url = {https://comsys.rwth-aachen.de/fileadmin/papers/2020/2020-pennekamp-supply-chain-privacy.pdf}, publisher = {IEEE}, booktitle = {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}, event_place = {Dublin, Ireland}, event_date = {June 7-11, 2020}, ISBN = {978-1-7281-7440-2}, ISSN = {2474-9133}, DOI = {10.1109/ICCWorkshops49005.2020.9145100}, reviewed = {1}, author = {Pennekamp, Jan and Bader, Lennart and Matzutt, Roman and Niemietz, Philipp and Trauth, Daniel and Henze, Martin and Bergs, Thomas and Wehrle, Klaus} } @Article { 2020_gleim_factDAG, title = {FactDAG: Formalizing Data Interoperability in an Internet of Production}, journal = {IEEE Internet of Things Journal}, year = {2020}, month = {4}, day = {14}, volume = {7}, number = {4}, pages = {3243-3253}, abstract = {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.}, keywords = {Data Management; Data Versioning; Interoperability; Industrial Internet of Things; Worldwide Lab}, tags = {internet-of-production}, url = {https://comsys.rwth-aachen.de/fileadmin/papers/2020/2020-gleim-iotj-iop-interoperability.pdf}, publisher = {IEEE}, ISSN = {2327-4662}, DOI = {10.1109/JIOT.2020.2966402}, reviewed = {1}, author = {Gleim, Lars and Pennekamp, Jan and Liebenberg, Martin and Buchsbaum, Melanie and Niemietz, Philipp and Knape, Simon and Epple, Alexander and Storms, Simon and Trauth, Daniel and Bergs, Thomas and Brecher, Christian and Decker, Stefan and Lakemeyer, Gerhard and Wehrle, Klaus} } @Article { 2019-unterberg-matclass, title = {In-situ material classification in sheet-metal blanking using deep convolutional neural networks}, journal = {Production Engineering}, year = {2019}, month = {11}, day = {13}, volume = {13}, number = {6}, pages = {743-749}, keywords = {internet-of-production}, DOI = {10.1007/s11740-019-00928-w}, reviewed = {1}, author = {Unterberg, Martin and Niemietz, Phillip and Trauth, Daniel and Wehrle, Klaus and Bergs, Thomas} } @Inproceedings { 2019_pennekamp_dataflows, title = {Dataflow Challenges in an Internet of Production: A Security \& Privacy Perspective}, year = {2019}, month = {11}, day = {11}, pages = {27-38}, abstract = {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.}, keywords = {Internet of Production; dataflows; Information Security}, tags = {internet-of-production}, url = {https://www.comsys.rwth-aachen.de/fileadmin/papers/2019/2019-pennekamp-dataflows.pdf}, publisher = {ACM}, booktitle = {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}, event_place = {London, United Kingdom}, event_date = {November 11-15, 2019}, ISBN = {978-1-4503-6831-5/19/11}, DOI = {10.1145/3338499.3357357}, reviewed = {1}, author = {Pennekamp, Jan and Henze, Martin and Schmidt, Simo and Niemietz, Philipp and Fey, Marcel and Trauth, Daniel and Bergs, Thomas and Brecher, Christian and Wehrle, Klaus} } @Inproceedings { 2019_pennekamp_infrastructure, title = {Towards an Infrastructure Enabling the Internet of Production}, year = {2019}, month = {5}, day = {8}, pages = {31-37}, abstract = {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.}, keywords = {Internet of Production; Cyber-Physical Systems; Data Processing; Low Latency; Secure Industrial Collaboration}, tags = {internet-of-production}, url = {https://www.comsys.rwth-aachen.de/fileadmin/papers/2019/2019-pennekamp-iop-infrastructure.pdf}, publisher = {IEEE}, booktitle = {Proceedings of the 2nd IEEE International Conference on Industrial Cyber-Physical Systems (ICPS '19), May 6-9, 2019, Taipei, TW}, event_place = {Taipei, TW}, event_date = {May 6-9, 2019}, ISBN = {978-1-5386-8500-6/19}, DOI = {10.1109/ICPHYS.2019.8780276}, reviewed = {1}, author = {Pennekamp, Jan and Glebke, Ren{\'e} and Henze, Martin and Meisen, Tobias and Quix, Christoph and Hai, Rihan and Gleim, Lars and Niemietz, Philipp and Rudack, Maximilian and Knape, Simon and Epple, Alexander and Trauth, Daniel and Vroomen, Uwe and Bergs, Thomas and Brecher, Christian and B{\"u}hrig-Polaczek, Andreas and Jarke, Matthias and Wehrle, Klaus} } @Inproceedings { 2019-glebke-hicss-integrated, title = {A Case for Integrated Data Processing in Large-Scale Cyber-Physical Systems}, year = {2019}, month = {1}, day = {8}, pages = {7252-7261}, tags = {internet-of-production,reflexes}, url = {https://www.comsys.rwth-aachen.de/fileadmin/papers/2019/2019-glebke-integrated.pdf}, misc2 = {Online}, publisher = {University of Hawai'i at Manoa / AIS}, booktitle = {Proceedings of the 52nd Hawaii International Conference on System Sciences (HICSS), Wailea, HI, USA}, language = {en}, ISBN = {978-0-9981331-2-6}, DOI = {10.24251/HICSS.2019.871}, reviewed = {1}, author = {Glebke, Ren{\'e} and Henze, Martin and Wehrle, Klaus and Niemietz, Philipp and Trauth, Daniel and Mattfeld, Patrick and Bergs, Thomas} }