Analysis of the fiber laydown quality in spunbond processes with simulation experiments evaluated by blocked neural networks

Gramsch, Simone, Sarishvili, Alex, Schmeißer, Andre

arXiv.org Machine Learning 

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.

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