CC BY-NC-ND 4.0Küfner, ThomasThomasKüfnerUhlemann, Thomas H.-J.Thomas H.-J.UhlemannZiegler, BastianBastianZiegler2022-03-0530.8.20182018https://publica.fraunhofer.de/handle/publica/25394610.1016/j.procir.2018.03.125In the course of digitization, a drastically increased amount of acquired data in production systems can be observed. Nevertheless, only a minor part of the acquired data is practically used for near real-time analysis and optimization within production systems. This paper introduces a concept for the realization of a decentralized data analysis integration. Therefore, an analysis system using artificial neural networks is conducted at the measurement point in the main supply of a production plant, to classify different operating states. The classification accuracy in all evaluation models is at least 99.82% and proves that it is capable to recognize the operating states of a production machinery reliably. The significantly, without loss of information, reduced amount of data is handed over to a superordinate instance of the production system for further use of data.enneuronales NetzwerkDigitalisierungKünstliche IntelligenzFertigungintelligente Produktionjournal article