Klassifizierung von Schmiedeteilen mittels KNN: KI erlaubt automatisierte Erkennung und Einteilung von geometrischen komplexen Schmiedebauteilen

Research output: Contribution to journalArticleResearch

Authors

  • Yorck Hedicke-Claus
  • Jan Langner
  • Malte Stonis
  • Bernd Arno Behrens

External Research Organisations

  • Institut für integrierte Produktion Hannover (IPH)
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Details

Translated title of the contributionAI enables automated recognition and classification of geometrically complex forged parts
Original languageGerman
Pages (from-to)822-827
Number of pages6
Journalwt Werkstattstechnik online
Volume109
Issue number11-12
Publication statusPublished - 2019

Abstract

This paper presents a method for the automated classification of forged parts for classification into the Spies order of shapes by artificial neural networks.The aim is to develop a recognition program within the framework of automated forging sequence planning, which can directly identify a shape class from the CAD file of the forged part and characteristics of the forged part relevant for the design of the process.

ASJC Scopus subject areas

Cite this

Klassifizierung von Schmiedeteilen mittels KNN: KI erlaubt automatisierte Erkennung und Einteilung von geometrischen komplexen Schmiedebauteilen . / Hedicke-Claus, Yorck; Langner, Jan; Stonis, Malte et al.
In: wt Werkstattstechnik online, Vol. 109, No. 11-12, 2019, p. 822-827.

Research output: Contribution to journalArticleResearch

Hedicke-Claus Y, Langner J, Stonis M, Behrens BA. Klassifizierung von Schmiedeteilen mittels KNN: KI erlaubt automatisierte Erkennung und Einteilung von geometrischen komplexen Schmiedebauteilen . wt Werkstattstechnik online. 2019;109(11-12):822-827. doi: 10.37544/1436-4980-2019-11-12-24
Hedicke-Claus, Yorck ; Langner, Jan ; Stonis, Malte et al. / Klassifizierung von Schmiedeteilen mittels KNN : KI erlaubt automatisierte Erkennung und Einteilung von geometrischen komplexen Schmiedebauteilen . In: wt Werkstattstechnik online. 2019 ; Vol. 109, No. 11-12. pp. 822-827.
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abstract = "This paper presents a method for the automated classification of forged parts for classification into the Spies order of shapes by artificial neural networks.The aim is to develop a recognition program within the framework of automated forging sequence planning, which can directly identify a shape class from the CAD file of the forged part and characteristics of the forged part relevant for the design of the process.",
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