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DATA MINING APPLICATIONS IN MANUFACTURING OF LIGHTWEIGHT STRUCTURES

Part of the Zukunftstechnologien für den multifunktionalen Leichtbau book series (ZML)

Abstract

Advanced manufacturing of automotive lightweight structures implies the introduction of new process steps into traditional process chains. Due to the combination of materials and their functional integration, those process steps show increased complexity. As a result, manufacturing faces new challenges regarding a constant and high product quality. A widely discussed approach to encounter these new challenges is the analysis of manufacturing process data by applying data mining methods. Benefits of the underlying digitalization approach are found in extensive transparency, product quality assurance, decision support or even in an automated manufacturing control.

Application fields of data mining in manufacturing of lightweight structures, the design of an appropriate context-based data acquisition infrastructure and special aspects of lightweight structures manufacturing influencing the CRISP-DM data mining workflow are discussed. The application of machine state recognition in extrusion of a glass fiber reinforced plastic rib structure exemplifies the proposed aspects.

Keywords

  • Data mining
  • Lightweight structures
  • Shop floor data acquisition
  • Machine state recognition

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  • DOI: 10.1007/978-3-662-58206-0_2
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Correspondence to Sebastian Gellrich .

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Gellrich, S., Filz, MA., Wölper, J., Herrmann, C., Thiede, S. (2019). DATA MINING APPLICATIONS IN MANUFACTURING OF LIGHTWEIGHT STRUCTURES. In: Dröder, K., Vietor, T. (eds) Technologies for economical and functional lightweight design. Zukunftstechnologien für den multifunktionalen Leichtbau. Springer Vieweg, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-58206-0_2

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  • DOI: https://doi.org/10.1007/978-3-662-58206-0_2

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  • Publisher Name: Springer Vieweg, Berlin, Heidelberg

  • Print ISBN: 978-3-662-58205-3

  • Online ISBN: 978-3-662-58206-0

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