% % This file was created by the TYPO3 extension % bib % --- Timezone: CET % Creation date: 2024-03-29 % Creation time: 09-03-38 % --- Number of references % 2 % @Article { 2022_brauner_iop, title = {A Computer Science Perspective on Digital Transformation in Production}, journal = {ACM Transactions on Internet of Things}, year = {2022}, month = {5}, day = {1}, volume = {3}, number = {2}, abstract = {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.}, keywords = {Internet of Production; World Wide Lab; Digital Shadows; Industrial Internet of Things}, tags = {internet-of-production}, url = {https://www.comsys.rwth-aachen.de/fileadmin/papers/2022/2022-brauner-digital-transformation.pdf}, publisher = {ACM}, ISSN = {2691-1914}, DOI = {10.1145/3502265}, reviewed = {1}, author = {Brauner, Philipp and Dalibor, Manuela and Jarke, Matthias and Kunze, Ike and Koren, Istv{\'a}n and Lakemeyer, Gerhard and Liebenberg, Martin and Michael, Judith and Pennekamp, Jan and Quix, Christoph and Rumpe, Bernhard and van der Aalst, Wil and Wehrle, Klaus and Wortmann, Andreas and Ziefle, Martina} } @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} }