KIT | KIT-Bibliothek | Impressum | Datenschutz

Automated Identification of Components of Feed Axes

Puchta, Alexander 1; Frisch, Marvin 1; Fleischer, Jürgen 1
1 Institut für Produktionstechnik (WBK), Karlsruher Institut für Technologie (KIT)

Abstract (englisch):

Monitoring solutions like simulation models and digital twins enable methods like predictive maintenance, cutting down on idle time and improving the effectiveness and lifetime of machine tools. Creating these models for brown-field equipment is therefore sensible from both an ecological and economical view. Designing them, however, is a time-consuming process that requires a lot of expertise. Automating this has the potential to increase both the number and the quality of models. This paper presents an approach to automatically identify the parts of the feed axes of machine tools based on reference runs. For this, the control signals of exemplary machines are analyzed in order to develop a rule-based system to differentiate variations of parts. Furthermore, approximations of certain system parameters like gear ratios are determined. This constitutes a first step towards fully automated generation of functional models.


Zugehörige Institution(en) am KIT Institut für Produktionstechnik (WBK)
Publikationstyp Proceedingsbeitrag
Publikationsmonat/-jahr 11.2024
Sprache Englisch
Identifikator ISBN: 978-3-031-47395-1
ISSN: 2194-0525
KITopen-ID: 1000165234
Erschienen in Production at the Leading Edge of Technology. Hrsg.: T. Bauernhansl
Veranstaltung 13th Congress of the German Academic Association for Production Technology (WGP) (2023), Freudenstadt, Deutschland, 20.11.2023 – 23.11.2023
Verlag Springer Nature Switzerland
Seiten 143–151
Serie Lecture Notes in Production Engineering
Vorab online veröffentlicht am 18.11.2023
Schlagwörter Digital manufacturing system; Identifcation; Machine tool
Nachgewiesen in Scopus
Dimensions
KIT – Die Forschungsuniversität in der Helmholtz-Gemeinschaft
KITopen Landing Page