Along with the trend of automation in textile industry, an objective, correct and efficient fiber identification method has become an important indicator in having a rapid respondent system that textile industry strives for. By applying stain test and artificial neural network, a prediction model for non-woven blending ratio has been developed in this study. As shown in the study results, the correct classification of the classification model for 10 non-woven fabrics, including C/PET, C/W, C/PAN, C/N, W/PET, W/PAN, WIN, PET/PAN, PET/N and PAN/N, developed by adopting CIE XYZxy values was nothing less than perfection. Then, by further adopting CIE XYZxy color values, 10 prediction models for non-woven blending ratio were established individually. The high correlation coefficient of more than 0.99 between the actual blending ratio and its predicted value of each model clearly indicated the strong fitted ability of all models.

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In order to add higher value to spun yarns, we have studied the application of a twist draft spinning to multi -kind small-lot production of functional yams. In twist draft spinning, a yarn is spun out directly from a large mass of material fiber and the yam count is controlled by spun yam tension. In this paper, we specially have regard to the linear de n-sity and twist rate of the yarn those are deeply concerned with quality of the yam. Through an analysis of the yam properties, it is found that the density of material fiber mass is the most effective parameter in properties of material fiber to adjust twist factor of the yarn. Furthermore, the linear density and the twist factor of the yam can be controlled independently by using spun yam tension and density of material fiber mass as adjusting parameters.

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In order to make the frictional strength of entanglement of interlaced yams clear, interlaced yarns were subjected to iterative frictional forces by reciprocating rubbers and afterward their number of tangles was measured. The frictional strength of entanglement is defined as the ratio of the number of residual tangles to that of original ones. The number of fractions, friction angle, static tension, friction speed, and kind of yarns were used as experimental factors. As a result, when the number of fractions, friction angle, static tension and friction speed are large, tangling parts are easily destroyed. The yarn with more filaments or larger fineness shows a larger frictional strength of entanglement.

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In the polymer processing operations of extrusion and blow molding, weld-lines often occur on the product, especially on the parison made by extruding polymer melts. This is because the polymer molecules near the weld-line highly orient owing to the elongational flow and the molecular orientation does not relax. In the present paper, the non-isothermal viscoelastic welding flow in the channel with a spider that supports a mandrel was numerically calculated for analyzing the molecular orientation in the weld-line region. The single-mode Giesekus model was used as a constitutive equation. The effect of the temperature on the velocity, the stress and the molecular orientation in the stress relaxation process at the weld-line was analyzed. The calculations were carried out for the channel wall temperatures T_w=190, 195, 200, and 205°C at the inlet temperature T_l=190°C. The numerical results showed that the overshoot of the velocity along the centerline downstream of the spider was large when the channel wall temperature was high. For a fluid with remarkable shear-thinning property, the spider with a large rear-end-angle suppressed the overshoot in the case of T_w=205°C. When the wall temperature was high, the distance necessary for relaxation of molecular orientation were short, thus little anisotropy remained in the weld region after solidification.

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