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  4. Potentials of Industrie 4.0 and Machine Learning for Mechanical Joining
 
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2017
Conference Paper
Title

Potentials of Industrie 4.0 and Machine Learning for Mechanical Joining

Other Title
Potenziale von Industrie 4.0 und Maschinellem Lernen für die Mechanische Fügetechnik
Abstract
-Sensitivity analysis of the influence of component properties and joining parameters on the joining result for self-pierce riveting -Possibilities to link mechanical joining technologies with the automotive process chain for quality and flexibility improvements -Potential of using machine learning to reduce automotive product development cycles in relation to mechanical joining -Datamining for machine learning at mechanical joining
Author(s)
Jäckel, Mathias  
Fraunhofer-Institut für Werkzeugmaschinen und Umformtechnik IWU  
Mainwork
Joining in Car Body Engineering 2017. Reducing Complexity - Enabling lightweight design  
Conference
Conference "Joining in Car Body Engineering" 2017  
File(s)
Download (5.59 MB)
Rights
Use according to copyright law
DOI
10.24406/publica-fhg-396138
Language
English
Fraunhofer-Institut für Werkzeugmaschinen und Umformtechnik IWU  
Keyword(s)
  • mechanical joining

  • FEM-Simulation

  • machine learning

  • Industrie 4.0

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