Prediction of Fiber Diameter of Melt Blown Nonwovens Produced by Sharp Die Using Neural Network Theory

摘要

Melt blowing is known for directly converting polymer resin into nonwoven fabrics of microfibers. The fiber diameter of melt blown nonwoven fabrics is strongly influenced by the air jet flow field developed from the sharp die. The dual slot sharp die is often used to yield polymer fibers in this process. The objective of this paper is to investigate the fiber diameter of melt blowing nonwovens produced by sharp die using an artificial neural network model. The fiber diameter of melt blowing nonwoven is mostly influenced by processing parameters (polymer flow rate, polymer melt temperature, initial air velocity, die-to-collector distance and initial air temperature). By analyzing the results obtained with the aid of the ANN model, the effects of melt blowing process parameters on the fiber diameter can be predicted. The results demonstrate that ANN model is a effective and a excellent method for predictors.