publication . Other literature type . Conference object . 2019 . Embargo end date: 30 Sep 2019

Machine Learning for CFRP Quality Control

Zambal, Sebastian; Heindl, Christoph; Eitzinger, Christian;
Embargo
  • Published: 18 Sep 2019
  • Publisher: Zenodo
Abstract
<strong>Abstract</strong> - Automation in CFRP production poses multiple challenges. The material at hand is very un-isotropic and deformable, leading to various difficulties in handling. We believe that visual inspection and quality control are key technologies to improve automation in CFRP production. In this paper, we point out possible ways to exploit modern machine learning methods in the context of CFRP quality control. Taking the example of AFP, we show how to transform prior knowledge about the production process into a probabilistic model. By drawing samples from this model, we demonstrate how to infer hidden variables of the process efficiently. We sho...
Funded by
EC| ZAero
Project
ZAero
Zero-defect manufacturing of composite parts in the aerospace industry
  • Funder: European Commission (EC)
  • Project Code: 721362
  • Funding stream: H2020 | IA
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Conference object . 2019
Provider: ZENODO
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Other literature type . 2019
Provider: Datacite
Zenodo
Other literature type . 2019
Provider: Datacite
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publication . Other literature type . Conference object . 2019 . Embargo end date: 30 Sep 2019

Machine Learning for CFRP Quality Control

Zambal, Sebastian; Heindl, Christoph; Eitzinger, Christian;