Rissrisikovorhersage für ein Musterungsdesign zur Verwendung bei der Musterung von Faserbasiertem Verpackungsmaterial

Details

Veröffentlichungs-Nr.

EP4764936

Anmeldetag

26. September 2025

Veröffentlichung

24. Juni 2026

Rechtsraum

EP

IPC

G06F30/23, G06F30/27

Abstract

The present invention relates to training a machine learning model to predict a relative crack index, RCI, map for a candidate fiberboard patterning design to be used in patterning of fiberboard packaging material. The training comprises: generating a training dataset for the machine learning model by, for each of a plurality of training fiberboard patterning designs, 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 fiberboard patterning designs 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 fiberboard patterning design.

Anmelder

Firma

Tetra Laval Holdings & Finance S.A.

Land

🇨🇭 Schweiz