Abstract
In this paper, a computer aided system for designing nonwoven materials is presented. As an original approach in the field of nonwoven research, both quality measurement analysis and human knowledge processing are integrated in the system. It allows designers to optimize the structure of nonwoven materials with limited trials according to the functional properties given in customers’ specifications. This system aims at modeling the relation between functional or physical properties (outputs) and structural parameters (inputs) of nonwoven products. In order to reduce the complexity of the system, a procedure is proposed for selecting the most relevant input variables based on a ranking criterion, which takes into account both the expertise of manufacturers and the measured data. In this criterion, fuzzy logic is used to establish a good compromise or a fusion between these two uncertain and incomplete information sources. Then, two models are set up by utilizing multilayer feed forward neural networks, which take into account the generality and the specificity of the product families respectively. The presented models have been validated with the use of experimental data concerning several families of nonwoven products.