Sensorlose Überwachung der Einzelteilfertigung/Spindle-current-based process monitoring using artificial intelligence

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OriginalspracheDeutsch
Seiten (von - bis)305-308
Seitenumfang4
Fachzeitschriftwt Werkstattstechnik online
Jahrgang111
Ausgabenummer5
PublikationsstatusVeröffentlicht - 2021

Abstract

Spindle current measurement allows acquiring process information without the need for additional sensors. Digital machine controls allow accessing the data with low effort. However, precise classification of process errors is a non-trivial task, especially for complex, single item workpieces without reference data. This work presents an approach to predict the spindle current and calculate tolerance limits by using a neuronal network based on a material removal simulation.

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Sensorlose Überwachung der Einzelteilfertigung/Spindle-current-based process monitoring using artificial intelligence. / Denkena, Berend; Bergmann, Benjamin; Becker, Jonas et al.
in: wt Werkstattstechnik online, Jahrgang 111, Nr. 5, 2021, S. 305-308.

Publikation: Beitrag in FachzeitschriftArtikelForschungPeer-Review

Denkena B, Bergmann B, Becker J, Blech H. Sensorlose Überwachung der Einzelteilfertigung/Spindle-current-based process monitoring using artificial intelligence. wt Werkstattstechnik online. 2021;111(5):305-308. doi: 10.37544/1436-4980-2021-05-39
Denkena, Berend ; Bergmann, Benjamin ; Becker, Jonas et al. / Sensorlose Überwachung der Einzelteilfertigung/Spindle-current-based process monitoring using artificial intelligence. in: wt Werkstattstechnik online. 2021 ; Jahrgang 111, Nr. 5. S. 305-308.
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