Einsatz eines Digitalen Zwillings zur Prozessoptimierung und prädiktiven Instandhaltung

Benedikt Schmucker; Johannes Ellinger; Maximilian Benker; Thomas Semm; Michael F. Zäh

doi:10.3139/104.112303

Einsatz eines Digitalen Zwillings zur Prozessoptimierung und prädiktiven Instandhaltung

Translated title of the contribution: Use of a digital twin for process optimization and predictive maintenance using the machine tools as example

Benedikt Schmucker, Johannes Ellinger, Maximilian Benker, Thomas Semm, Michael F. Zäh

Chair of Machine Tools and Manufacturing Technology

Research output: Contribution to journal › Article › peer-review

2 Scopus citations

Abstract

The economic use of machine tools is highly dependent on the material removal rate and the amount of machine downtime. As a result, manufacturing companies focus on increasing feed rates and cutting depths and on reducing the number of necessary maintenance measures. The digital twin enables the optimization of machining processes, while obeying the static and dynamic load limits, through a permanent data exchange between the real machine tool and its virtual representation. Additionally, the acquisition of data during the lifetime of machine tools allows to detect changes in the dynamic behaviour of the feed drive components. Variations of the determined modal parameters indicate changes in the wear condition. By means of a probabilistic classification its future progression can be forecasted.

Translated title of the contribution	Use of a digital twin for process optimization and predictive maintenance using the machine tools as example
Original language	German
Pages (from-to)	78-83
Number of pages	6
Journal	ZWF Zeitschrift fuer Wirtschaftlichen Fabrikbetrieb
Volume	115
DOIs	https://doi.org/10.3139/104.112303
State	Published - Apr 2020

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abstract = "The economic use of machine tools is highly dependent on the material removal rate and the amount of machine downtime. As a result, manufacturing companies focus on increasing feed rates and cutting depths and on reducing the number of necessary maintenance measures. The digital twin enables the optimization of machining processes, while obeying the static and dynamic load limits, through a permanent data exchange between the real machine tool and its virtual representation. Additionally, the acquisition of data during the lifetime of machine tools allows to detect changes in the dynamic behaviour of the feed drive components. Variations of the determined modal parameters indicate changes in the wear condition. By means of a probabilistic classification its future progression can be forecasted.",

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AU - Zäh, Michael F.

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Einsatz eines Digitalen Zwillings zur Prozessoptimierung und prädiktiven Instandhaltung

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