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- W4313532831 abstract "The study aims to examine the challenges and approaches to intelligent monitoring in diversified automated manufacturing in the context of its digitalization as well as to provide a quality monitoring case based on neural networks. Perspectives of artificial neural networks application to real-time monitoring the produced part quality are discussed. The analysis of network structures and a number of algorithms prove that a counter-propagation network can be used as the selected neural network. The work proposes a modification of the counter-propagation network topology for solving the problem of determining the quality parameters of a manufactured part, as well as a structure for intelligent machining quality monitoring. The paper analyzes the challenges of intelligent monitoring in digitalized diversified automated production. A system for intelligent quality monitoring based on neural networks (counter-propagation network) has been developed. Real time quality monitoring together with the control correction will ensure the improved quality and will make the manufacturing as a whole more efficient." @default.
- W4313532831 created "2023-01-06" @default.
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- W4313532831 date "2023-01-01" @default.
- W4313532831 modified "2023-09-27" @default.
- W4313532831 title "Intelligent Monitoring System Formation in Modern Production in the Context of Manufacturing Digitalization" @default.
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- W4313532831 doi "https://doi.org/10.1007/978-3-031-21438-7_49" @default.
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