On the Way to the Autonomous Machine Automatic Parameterization of a Lifelong and individual Model of the Machine Dynamic Behavior of a Milling Machine

被引：0

作者：

Oexle F. ^{[1
]}

Fleischer J. ^{[1
]}

机构：

[1] Wbk Institut für Produkionstechnik, Karlsruher Institut für Technologie (KIT), Kaiserstr. 12, Karlsruhe

来源：

ZWF Zeitschrift fuer Wirtschaftlichen Fabrikbetrieb | 2023年 / 118卷 / 1-2期

关键词：

Artificial Intelligence; Industry; 4.0; Machine Dynamic Behavior; Machine Tools; Neural Networks; Parameter Identifier;

D O I：

10.1515/zwf-2023-1016

中图分类号：

学科分类号：

摘要：

In the context of Industry 4.0, the features of production machines are becoming increasingly comprehensive thanks to digital services. Among other things, the focus is on the prediction of machine behavior. Currently, for example, the finite element method or multi-body simulations are used to map the machine's dynamic behavior. However, up to now there is no solution that digitally represents a machine throughout its lifetime and individually. In the following, a new approach is presented. © 2023 Walter de Gruyter GmbH, Berlin/Boston, Germany.

引用

页码：69 / 73

页数：4

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