Predicting the fibre diameter of melt blown nonwovens: comparison of physical, statistical and artificial neural network models

Abstract

Physical, statistical and artificial neural network (ANN) models are established for predicting the fibre diameter of melt blown nonwovens from the processing parameters. The results show that the ANN model yields a very accurate prediction (average error of 0.013%), and a reasonably good ANN model can be achieved with relatively few data points. Because the physical model is based on the inherent physical principles of the phenomena of interest, it can yield reasonably good prediction results when experimental data are not available and the entire physical procedure is of interest. This area of research has great potential in the field of computer assisted design in melt blowing technology.