In digital transformation, the entire value chain is networked across applications using technologies from the context of the Internet of Things (IoT). The associated complexity in software development increasingly requires interdisciplinary development of hardware, software and mathematical modelling. Individual sensors are linked to a digital twin that is able to communicate information about the measurement uncertainty. For traditional industrial measurement and calibration methods, the metrological quality infrastructure is based on accredited calibration equipment and standardized evaluation methods in order to assign measured values a quantitative statement about their reliability.
The overall objective of the FAMOUS project is the establishment of quantifiable statements on data quality in industry 4.0 with a flexible and practice-oriented implementation of mathematical models and procedures. For this purpose, robust mathematical and statistical models of the sensors used and their networking are to be developed.
which display existing information about the measuring devices in a suitable manner. By developing a modular and flexible software architecture based on edge and organic computing approaches, the methods can be used in real industrial 4.0 scenarios. This will be done in the project evaluated on the basis of selected test fields.