This study of two new total hand simulating methods for knits uses fuzzy theory and neural networks. One method, a neural network system trained with a back-propaga tion algorithm, performs functional mapping between mechanical properties and the resulting total hand values of the fuzzy predicting method. The second method, a fuzzy-neural network system, uses the fuzzy membership function, weighted factor vector, and error back-propagation algorithm. The principal mechanical properties of stretchiness, bulkiness, flexibility, distortion, weight, and surface roughness of the knitted fabrics are correlated with experimentally determined Kawabata total hand values and fuzzy transformed overall hand values. Fuzzy and neural networks agree better with the subjective test results than the KES-FB system. The mechanical prop erties are fuzzified by fuzzy membership functions, then trained to predict the total hand value of outerwear knitted fabrics. In each case, the prediction error is less than the standard deviation of experimentation, and the optimum structure is investigated. These two systems, which use the Pascal programming language, produce objective ratings of outerwear knit fabrics.

The mechanical and handle properties of three groups of double weft-knitted fabrics are measured using the KES-FB system. The double-jersey fabrics consist of double weft-knitted structures (knit, tuck, and welt stitches), and are further divided according to density and then fully relaxed. For hand measurements, seven principal physical and mechanical properties are selected (EMT, RT, RC, B, 2HG, w, MIU), which are related to four possible ways of deformation in double weft-knitted fabrics. The importance of their characteristics is deduced from a survey of a panel of thirty judges. Primary hand and total hand values from the KES-FB are analyzed and compared with our alternative simplified fuzzy total hand test result. The results from the new method for double weft-knitted fabrics provide experts with meaningful values in comparison with Ka wabata's total hand values.

This paper concentrated on the objective evaluation of total hand value in knitted fabrics using the theory of neural networks and the comparison of two methods. For the objective evaluation of overall hand feeling in knitted fabric, 47 kinds of weft-knitted and warp-knitted fabrics were manufactured. The optimum construction of neural networks was investigated through the change of layer and neuron number. For the comparison of the two methods, a subjective test was carried out. Two techniques, KES-FB system and neural network applied simulator, were compared using nine randomly selected knitted fabrics. These fabrics were used to show that the neural network adapted simulation method was in good agreement with subjective test results.

Two sets of single wool weft-knitted fabrics made from conventional yarn and lincLITE®, which was developed by the Wool Research Organization of New Zealand in an effort to make a softer and bulkier wool, are used to analyze a total hand evaluation model for outerwear knitted fabrics. Mechanical properties and total hand value are measured on the KES-FB system, and three kinds of fuzzy membership functions (a decreasing halfCauchy equation and two linear functions, increasing or decreasing) are used to calculate fuzzified overall hand values of the knitted fabrics. The weighted factor vectors surveyed by a Korean panel are strongly related to those of a New Zealand panel. Based on these surveys, we calculate the total hand value of the KES-FB and the fuzzy model. The latter results show that the bulkiness of single wool fabric knitted from lincLITE yarn is a little higher than the same fabric knitted from conventional yarn. Furthermore, the fuzzy total hand evaluation from the Korean panel is highly correlated with the result of the New Zealanders.Previous papers [20. 21 have reported on measurements and fuzzy models for double weft-knitted fabrics on the basis of seven mechanical properties. The hand of knitted fabrics can be affected by fiber type, yarn size, fabric structure, fabric geometry, and finish [1, 7. 9].There has been a great interest in hand evaluation due to the introduction of various kinds of knitted fabrics [ 1, 5, 6, l 1 ] and technical improvements of new synthetic or natural fibers [1, 6]. As new fibers and blends have developed, considerable work has focused on the physical and mechanical properties of fabrics, such as hand and drape [t. 6, 12, 14]. Considering the standardization of hand evaluation, a more effective link for hand is needed to predict the overall hand of knitted fabrics made from conventional and newly developed yarns.The Kawabata fabric evaluation system (KES-FB) provides an objective specification of hand value and total hand value on the basis of mechanical properties, but the system is not appropriate for knitted fabrics that have comparatively high flexibility and stretchiness [ 19]. However, mechanical properties such as bulkiness, flexibility, stretchiness, distortion, weight, and smoothness are recognized as important components for good comfort and quality knits [5,8,9,12,16,23]. Thus, an objective hand technique is needed for better evaluations of knitted fabrics.In this paper, we measure the mechanical properties of two knitted fabrics and then calculate the total hand value using the KES-FB system. We also analyze a fuzzy transformation function [20-23, 25, 26]. We focus on a fuzzy hand evaluation model and a comparison of total hand values by two evaluation methods for plain wool knitted fabrics of HncUTE~ and conventional yams. Experimental SPECIMEN PREPARATIONFor the study, single plain fabrics were knitted from two kinds of raw materials. lincLITE and conventional yam. Figures I is a representation of lincLITE yam. which was made from 100~c merino wool. A...

Abstract-This study was aimed to investigate the antibacterial efficiency of silver nano-particles and the dyeing properties of a brushed warp-knitted fabric. The properties of the brushed warp-knitted fabric containing silver nano-particle by field production processes were evaluated by analyzing its silver contents, antibacterial activity, color difference, exhaustion curve, fastness and tearing strength. Bacterial reduction ratio amounts to 91.4 and 99.9 for Staphylococcus aureus and Klebsiella pneumoniae respectively. As the brushed pile length of its fabrics is longer, the exhaution rate of disperse dye becomes higher. The brushing process of its fabrics reduces the tearing strength. The results indicate that the brushed warp knitted fabric containing silver nano-particle can be a practically promising product.