On-line estimation of key quality parameters in nonwoven production

In an industrial nonwoven production process, data related to spun-web quality including firmness, thickness, and weight are measured online. However, these measurements provide insufficient information about the spun-web quality. As a result, other parameters that give a better insight into the quality of the product have been employed. One of these parameters reveals the minimum force necessary to pull apart a given size of piece of spun-web. It is measured in a quality control laboratory by stretching the ends of a sample piece of spun-web to a high degree of tension. Since the laboratory measurements are infrequent and off-line, an on-line monitoring of product quality can hardly be carried out. Neural network-based virtual sensors are developed based on historical data that incorporate both online and off-line measurements. The virtual sensors provide estimates of key quality parameters at the measurement frequency of the on-line measurements. They are implemented at a production facility of Freudenberg Nonwovens KG in Germany and have been successfully employed for on-line quality monitoring