This file was created by the TYPO3 extension bib --- Timezone: CEST Creation date: 2024-04-19 Creation time: 17-17-26 --- Number of references 2 article 2022_brauner_iop ACM Transactions on Internet of Things 2022 5 1 3 2 The Industrial Internet-of-Things (IIoT) promises significant improvements for the manufacturing industry by facilitating the integration of manufacturing systems by Digital Twins. However, ecological and economic demands also require a cross-domain linkage of multiple scientific perspectives from material sciences, engineering, operations, business, and ergonomics, as optimization opportunities can be derived from any of these perspectives. To extend the IIoT to a true Internet of Production, two concepts are required: first, a complex, interrelated network of Digital Shadows which combine domain-specific models with data-driven AI methods; and second, the integration of a large number of research labs, engineering, and production sites as a World Wide Lab which offers controlled exchange of selected, innovation-relevant data even across company boundaries. In this article, we define the underlying Computer Science challenges implied by these novel concepts in four layers: Smart human interfaces provide access to information that has been generated by model-integrated AI. Given the large variety of manufacturing data, new data modeling techniques should enable efficient management of Digital Shadows, which is supported by an interconnected infrastructure. Based on a detailed analysis of these challenges, we derive a systematized research roadmap to make the vision of the Internet of Production a reality. Internet of Production; World Wide Lab; Digital Shadows; Industrial Internet of Things internet-of-production https://www.comsys.rwth-aachen.de/fileadmin/papers/2022/2022-brauner-digital-transformation.pdf ACM 2691-1914 10.1145/3502265 1 PhilippBrauner ManuelaDalibor MatthiasJarke IkeKunze IstvánKoren GerhardLakemeyer MartinLiebenberg JudithMichael JanPennekamp ChristophQuix BernhardRumpe Wilvan der Aalst KlausWehrle AndreasWortmann MartinaZiefle 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