Rissrisikovorhersage für eine Kombination von Musterdesign zur Verwendung bei der Musterung von Faserbasiertem Verpackungsmaterial und Materialmodellparametern

Details

Veröffentlichungs-Nr.

EP4764937

Anmeldetag

25. November 2025

Veröffentlichung

24. Juni 2026

Rechtsraum

EP

Abstract

The present invention relates to training a machine learning model to predict a relative crack index, RCI, map for a candidate combination of a paperboard patterning design and a paperboard material having a set of paperboard material model parameters, the candidate combination to be used in patterning of paperboard packaging material. The training comprises: generating a training dataset for the machine learning model by, for each training combination of one or more training paperboard patterning designs and one or more paperboard materials having a respective set of paperboard material model parameters, performing a finite element method simulation resulting in a respective training RCI map; and training the machine learning model by adjusting weights of the machine learning model using the training combinations of the training dataset as input and the training RCI maps of the training dataset as ground truth. A training apparatus for training the machine learning model is also presented as well as use of the machine learning model to predict a RCI map for a candidate paperboard patterning design.

Anmelder

Firma

Tetra Laval Holdings & Finance S.A.

Land

🇨🇭 Schweiz