% % This file was created by the TYPO3 extension % bib % --- Timezone: UTC % Creation date: 2024-10-06 % Creation time: 16-47-34 % --- Number of references % 4 % @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} }