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The low-stress and recovery properties of ring, rotor and MJS yarns spun from tencel-polyester and tencel-cotton fibre mix have been studied. In comparison with ring and MJS yarns, rotor-spun yarns are more bulky, possess low tensile energy and resilience, lower immediate elastic recovery and have higher delayed elastic recovery and permanent deformation. Ring- spun yarns, on the other hand, possess least decay but behave poorly during abrasion test for 200 cycles. An increase in tencel content in both tencel-polyester and tencel-cotton mixes produces a compact yarn with reduced abrasion resistance, structural integrity and tensile resilience, poor recovery properties, and higher tensile energy. Generally, tencel-polyester yarns display better low-stress characteristics, except the abrasion resistance. Recovery properties have been found to significantly deteriorate with the increase in amplitude of extension regardless of yarn structure. [ABSTRACT FROM AUTHOR]

The physical characteristics of tencel-polyester and tencel-cotton yarns spun on ring, rotor and air-jet spinning machines in relation to blend ratio and twist factor have been studied. It is observed that amongst ring, rotor and MJS yarns, the ring yarns are stronger, less rigid and possess higher work of rupture, whereas rotor yarns are more even, have fewer imperfections and less hairy regardless of fibre-mix. Also, rotor- spun yarns have higher extensibility than ring and MJS yarns for tencel-cotton mix. Further, tencel-polyester yarns yield more satisfactory results than the tencel-cotton yarns in terms of strength, breaking extension, evenness, imperfections and work of rupture. Increasing tencel content both in tencel-polyester and tencel-cotton fibre mix makes the yarn rigid and more hairy. [ABSTRACT FROM AUTHOR]

This paper presents a study of hybrid effect on mechanical properties of tencel blended ring-, rotor- and Murata jet spinning yarns. The tensile strength, breaking elongation, flexural rigidity and abrasion resistance of tencel-polyester and tencel-cotton blended yarns are examined and compared with the value predicted using linear and quadratic rule of mixture (ROM). It is observed that there is no significant hybrid effect on abrasion resistance of tencel-polyester mix yarns and tenacity and breaking extension of tencel-cotton mix yarns; hence, a linear ROM is found better in predicting the yarn properties. Further, for all yarn types, there is a significant hybrid effect on tenacity, breaking extension and flexural rigidity of tencel-polyester mixes and flexural rigidity and abrasion resistance of tencel-cotton mixes. A quadratic ROM model suits well for these yarns. Overall, it is found that there is a negative hybrid effect on tenacity and breaking extension whereas there is a positive hybrid effect on flexural rigidity for all the yarn samples irrespective of fibre and yarn type. The abrasion resistance has a mixed trend. Further, tencel-polyester yarns yield more satisfactory results than the tencel-cotton yarns in terms of strength and breaking extension but behave poorly during abrasion test for 200 cycles. Increasing tencel content both in tencel-polyester and tencel-cotton fibre-mix produces a rigid yarn with reduced abrasion resistance. [ABSTRACT FROM AUTHOR]

Stretch fabrics are used in manufacturing pressure garments to exert pressure over specific body parts in medical conditions like venous and lymphatic disorders, scar management, and bone and muscle injuries. The amount of therapeutic pressure required in each medical condition is different; therefore, there is a need to engineer the stretch properties of garments to match the requirements in each case. Limited information is available on the relationship between fabric properties and the pressure generated on the body. In this paper, an attempt has been made to study the effect of inlay yarn pre-tension at the time of manufacturing of stretch fabrics on the pressure generated by the garments. Results show that change in inlay pre-tension significantly changes the structural characteristics of the fabric but the load elongation behavior remains unchanged up to 100% extension. Pressure exerted on rigid cylindrical tubes increases with reduction factor of the fabric tube and the curvature of the cylinder. [ABSTRACT FROM PUBLISHER]

The yarn count spinning limits on DREF-3 friction spinning machines for viscose and cotton fibers and the change in yarn properties with progressive change in yarn count have been investigated. The spinning limits were tex 328-25 and tex 328-16 for viscose and cotton fibers respectively. The tenacity of viscose yarns was found to increase initially and then decrease as the count became finer. However for cotton the tenacity remained fairly constant over the range of counts produced. The required twist in the yarns increased continuously as the yarns became finer. Both the yarns however, showed exceptionally high value of breaking extension when the counts were very coarse. The twist values and diameters of both types of yarns were similar over the entire count range. [ABSTRACT FROM AUTHOR]

Dref-III polyester-wool blended friction yarns having different sheath compositions and structures were spun successfully on a friction spinning machine keeping polyester in core. The sheath composition and structure were changed by varying core content and selectively placing polyester and wool in different layers of sheath. The location of the constituent fibres in sheath was found to affect both twist and yarn diameter. All wool sheath resulted in a bulky yarn with low twist. [ABSTRACT FROM AUTHOR]

This paper reports a brief outline of artificial neural network (ANN) and reviews its application in yarn manufacturing process. The use of neural network in predicting process parameters from known and unknown combination of yarn properties has also been investigated. ANN has been found to be very efficient in predicting process parameters when property combinations are taken from actual observed data. However, when the property set is arbitrary, the predicting is poor. The importance of choosing a feasible combination of input parameters has been highlighted. [ABSTRACT FROM AUTHOR]

The migratory behaviour of core and sheath fibres in dref-III friction-spun yarns has been studied using the tracer fibre technique. It is observed that the fibre migration in these yarns is restricted to particular zones only, depending on the position of fibre feed. Core fibres exhibit minimum values of migration parameters. In sheath, the fibres fed nearer to the delivery end show comparatively larger values. The two streams seem to be interlacing in the radial zone of 0.2-0.4. An increase in suction pressure decreases the fibre migration in both core and sheath elements while a decrease in core content initially decreases it, followed by an increase. Further, the variations in yarn tenacity and breaking extension have also been explained in terms of these changes in migration parameters. [ABSTRACT FROM AUTHOR]

The section of "Artificial Neural Networks: Applications to Textiles," focuses on the application of artificial neural networks (ANN) to fabrics. Several studies on the neural network applications are presented. A study describes an experiment with 50/50 polyester-fibre/cotton blended yarns to analyse the dynamic response of a microprocessor-based slasher- monitoring unit. In another study, researchers patented a neural-network-based control device for a loom. Yet another study suggested a method for predicting garment drape with the help of ANN.

The section of "Artificial Neural Networks: Applications to Textiles," focuses on the application of artificial neural networks (ANN) to yarns. Several studies on the neural network applications are presented. A study describes an experiment in which twenty types of cotton were evaluated for 29 fibre properties. A neural network was trained with data from 700 spinnable and 700 unspinnable yarns to predict the spinnability from fibre properties and process parameters. Another study used a neural network to model the spinning process with 41 fibre properties and five machine parameters as input and nine yarn properties as output.

The effect of sheath fibre fineness and length on the tensile and bending properties of dref-3 friction yarn has been studied using polyester and acrylic fibres. Sheath fibre fineness influences the tenacity of polyester yarns significantly but not of acrylic yarns. With the decrease in fibre fineness the polyester yarn tenacity decreases as the number of sheath fibres declines and the corresponding wrappings become loose. For acrylic yarn, the effect is less pronounced as the fibre fineness was limited to only 2.22 dtex. The sheath fibre length mainly affects tenacity and extension of polyester yarns by changing the sheath fibre extent. However, the acrylic yarns remain unaffected as the sheath fibre extent does not change much with change in sheath fibre length. [ABSTRACT FROM AUTHOR]

Though artificial neural networks have been used in a wide range of textile-related problems, the potential of the networks for discerning the relative importance of the input parameters has never been tested. Nor does there exist any reliable technique for this purpose. In the work reported in the present paper, neural networks were first created for predicting ring-spun-cotton-yarn properties from a set of fibre properties measured on high-volume instruments (HVI). The relative importance of the input parameters was evaluated by using two different methods, namely, 'skeletonozation', a method reported in the literature for pruning neural networks, and a newly developed method based on first-order sensitivity analysis. The sensitivity analysis was found to work significantly better. [ABSTRACT FROM AUTHOR]

The twist structure of DREF-III friction-spun yarns has been studied by optical method. It is observed that the different layers of sheath fibres exhibit more or less the same average twist as observed in the fibre layers of DREF-II structures. However, under the identical spinning conditions this twist is lower than the twist in DREF-II yam structures and the use of coarser fibres further reduces it. The twist also shows a decreasing trend with the increase in fibre length from 25 mm to 44 mm followed by a slight increase thereafter. Core fibres, instead of being straight and parallel to the yam axis as generally expected, are seen to be twisted. Both the core and the sheath fibres twist values have been found to increase with the increase in suction pressure. A decrease in core content increases the core twist while the sheath twist drops after an initial increase. [ABSTRACT FROM AUTHOR]

Mulberry silk fabric has been degummed by using five different methods (acid, alkali, triethylamine, soap and enzyme) and the results compared in terms of handle properties. Low stress mechanical properties tested on the KESF system have been used to evaluate the hand values. Soap has been taken as the standard method of degumming and the other treatments have been compared with this method. Significant differences in the low stress properties have been observed for the different treatments. Soap, alkali and TEA methods score over the acid and enzymatic methods in terms of handle properties, low shear and surface properties characterise the acid and enzyme degummed samples indicating non-uniform removal of gum from the interlacing areas. The whiteness index has also been measured. [ABSTRACT FROM AUTHOR]

A study to characterize the structure of air-jet textured yarn in terms of its migration parameters has been carried out by using the tracer fibre technique. An attempt has been made to establish the relationship between the migration parameters and the properties of air-jet textured yarns using polyester (dry and wet textured), nylon (wet textured) and polypropylene (wet textured) yarns. Physical bulk, instability, loop size, loop frequency, tenacity, breaking elongation and initial modulus were measured for various air-jet textured yarns produced using different air pressures. Migration was found to be highest in polyester (wet textured) yarns followed by wet textured polypropylene and nylon yarns. It was observed that physical bulk, loop frequency and initial modulus increases with increasing migration parameters, while tenacity, instability and breaking elongation decreases with migration parameters. Yarns produced from all three materials show similar trends. Bearing in mind the differences in dpf, the polyester feed materials showed relatively higher migration and better properties. [ABSTRACT FROM AUTHOR]

The article discusses the wicking behavior of compact and ring spun yarns and fabrics. There are many products where wicking plays a critical role in its performance. For example, transporting perspiration from wet skin for quick evaporation in the case of undergarments, wicking oil for lightening lamps, spreading spin of finish on synthetic fibers or filaments, absorption of water or fluid by towel, cleaning cloth, diapers, gauge and bandages. Spun yarns especially made from cotton are used in many of these applications. Wicking, which is the result of capillary flow in yarns, is governed by three important factors. They are fiber parameters, liquid properties and yarn structure. The fiber parameters are fiber surface characteristics, fineness, shape, swelling potential, strength and resilience in a wet state.

The section of "Artificial Neural Networks: Applications to Textiles," focuses on the application of artificial neural networks (ANN) to man-made fibers. Several studies on the neural network applications are presented. In a study, researchers developed neural networks to formulate structure-property relationships for the glass transition temperature (Tg) of amorphous and semi-crystalline polymers. Another study reported the feasibility of the application of neural networks for modelling the meitbiown process. Yet another study discussed the feasibility of using neural networks to predict false-twist-textured-yarn characteristics from machine settings.

The section of "Artificial Neural Networks: Applications to Textiles," focuses on the scope for further research in the application of Artificial Neural Networks (ANN) in the textile field. It is stated that there are some areas which have not yet fully explored. Such areas are knitting, non-woven fabrics, and colorimetry. Research on neural networks is moving rapidly. A major research area is fault identification in fabrics. It is opined that many of the techniques that are being used need feature-extraction procedures before the data can be fed to a neural network.