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An Architectural Design for Measurement Uncertainty Evaluation in Cyber-Physical Systems
Citation key VonPilchau2020
Author von Pilchau, Wenzel Pilar and Gowtham, Varun and Gruber, Maximilian and Riedl, Matthias and Koutrakis, Nikolaos-Stefanos and Tayyub, Jawad and Hähner, Jörg and Eichstädt, Sascha and Uhlmann, Eckart and Polte, Julian and Frey, Volker and Willner, Alexander
Title of Book 15th Conference on Computer Science and Information Systems (FedCSIS)
Year 2020
Month aug
Abstract Several use cases from the areas of manufacturing and process industry, require highly accurate sensor data. As sensors always have some degree of uncertainty, methods are needed to increase their reliability. The common approach is to regularly calibrate the devices to enable traceability according to national standards and Syst$\backslash$`eme international (SI) units - which follows costly processes. However, sensor networks can also be represented as Cyber Physical Systems (CPS) and a single sensor can have a digital representation (Digital Twin) to use its data further on. To propagate uncertainty in a reliable way in the network, we present a system architecture to communicate measurement uncertainties in sensor networks utilizing the concept of Asset Administration Shells alongside methods from the domain of Organic Computing. The presented approach contains methods for uncertainty propagation as well as concepts from the Machine Learning domain that combine the need for an accurate uncertainty estimation. The mathematical description of the metrological uncertainty of fused or propagated values can be seen as a first step towards the development of a harmonized approach for uncertainty in distributed CPSs in the context of Industrie 4.0. In this paper, we present basic use cases, conceptual ideas and an agenda of how to proceed further on.
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