Quality Analysis And Prediction Of The Yarn

China' s entry into the WTO has brought her textile industry entirely new challenges as well as a rare chance for development. In order to adapt to the various problems in the changes of business management and modes of production accompanying market globalization, China' s textile industry must try, above all, to increase competitiveness for its survival and development, and the improvement and guarantee of the quality of its products should be of vital importance for this purpose.The lagging growth and the backward methods seen in the quality control system, and particularly in the quality prediction system of the textile trade, have, to a certain extent, restricted the sustainable development of the textile industry.Starting with the analysis of the production process of spinning, this article expounds how raw cotton, as an essential factor other than the production system and the technological parameters of spinning, plays a decisive role in affecting the quality of the yarn. The article further analyses the great effects produced by the quality of raw cotton on the technological parameters of spinning and the quality of the yarn, and points out that it is of great practical value to predict the quality of the finished yarn by means of the quality of raw cotton. Through interrelated analysis of the quality indexes of raw cotton and those of the finished yarn, the author was able to determine the interrelatedness and its degree among the various elements, and has, with the use of the artificial neural network, constructed a model neural network to predict the quality of the yarn by means of the quality indexes of raw cotton. The model neural network rationally indicates the relationship between the quality of raw cotton andthat of the yarn, thus accomplishing the accurate prediction of the quality of the finished yarn.The article reveals the fact in essence that raw cotton proves to be one of the major factors which affect the quality of the finished yarn, and , by applying the artificial neural network technology—the newly-rising frontier science based on the latest achievements of the neuroscientific researches, accomplishes the prediction of the quality of the finished yarn by means of that of raw cotton.