Analysis of the fiber laydown quality in spunbond processes with simulation experiments evaluated by blocked neural networks
Machine Learning
2020-01-23 v2 Machine Learning
Abstract
We present a simulation framework for spunbond processes and use a design of experiments to investigate the cause-and-effect-relations of process and material parameters onto the fiber laydown on a conveyor belt. The virtual experiments are analyzed by a blocked neural network. This forms the basis for the prediction of the fiber laydown characteristics and enables a quick ranking of the significance of the influencing effects. We conclude our research by an analysis of the nonlinear cause-and-effect relations.
Keywords
Cite
@article{arxiv.1911.06213,
title = {Analysis of the fiber laydown quality in spunbond processes with simulation experiments evaluated by blocked neural networks},
author = {Simone Gramsch and Alex Sarishvili and Andre Schmeißer},
journal= {arXiv preprint arXiv:1911.06213},
year = {2020}
}
Comments
12 pages, 23 figures