Search results

Looks at the eighth published year of the ITCRR and the research, from far and near, involved in this. Muses on the fact that, though all the usual processes are to the fore, the downside part of the industry is garment making which is the least developed side. Posits that the manufacture of clothing needs to become more technologically advanced as does retailing. Closes by emphasising support for the community in all its efforts.

Discusses the 6th ITCRR, its breadth of textile and clothing research activity, plus the encouragement given to workers in this field and its related areas. States that, within the newer research areas under the microscope of the community involved, technical textiles focuses on new, ‘smart’ garments and the initiatives in this field in both the UK and the international community at large. Covers this subject at length.

The purpose of this paper is to design woven fabrics with desired quality and low manufacturing cost by optimizing the weave parameters such as count, crimp and thread spacing of warp and weft yarns.

To fulfill this goal, the authors endeavor to devise a searching mechanism based on particle swarm optimization (PSO) for efficiently finding the appropriate combination of weave parameters.

The experimental validation confirms that the proposed method has an excellent search capacity to obtain the best combinations of weave parameters for producing the fabrics with requisite quality at low cost.

The quick response capability of the system would benefit the fabric manufacturers for efficient determination of the required weaving parameters to produce the engineered fabrics.

This paper offers a maiden application of PSO technique to design engineered products in textiles. The method is easy to implement and it is computationally inexpensive as fewer parameters are involved.

This paper presents a comprehensive review of soft computing applications in the domain of fabrics and clothing. In the last two decades, soft computing techniques, such as artificial neural network, fuzzy logic and genetic algorithm, have been used abundantly for fabrics and clothing modelling, manufacturing, quality control and marketing. This review is aimed at presenting a compendium of research work done so far on the applications of soft computing techniques in fabrics and clothing science and engineering. In the beginning of the paper, a brief introduction of soft computing techniques is provided. Then, the applications of soft computing methods in fabric property modelling (tensile, bending, shear, drape, handle, comfort, thickness and compression, air permeability, porosity, etc.) are provided. In the subsequent sections, soft computing applications for fabric defect identification in static and dynamic conditions, fabric classification, fabric engineering, machine control and marketing, are discussed. The scope of future applications is included in the concluding section.

The thermophysiological comfort of fabrics is prerequisite as customers covet adequate moisture, heat management-supported and UV protective clothing that measure up to their levels of activities and environmental conditions. Hitherto, scant tasks have been reported with the purpose of engineering both comfort and UV protection simultaneously. From that vantage point, the objective of this work is to develop a model for optimum UPF, air permeability, water-vapour resistance, thermal resistance, thermal absorptivity and areal density of knitted fabrics.

Weft knitted fabrics of various compositions were investigated. UPF was tested using the Labsphere UV transmittance analyser. The FX 3300 (Textest instruments) air permeability tester was used to test air permeability. Thermal comfort and water-vapour resistance were evaluated using the Alambeta and Permetest instruments, respectively. Based on image processing, the porosity was measured. Fabrics thickness and areal density were measured according to standard methods. Furthermore, parametric and non-parametric statistical test methods were applied to the data for analysis.

Linear regression was substantiated by Kolmogorov-Smirnov test. Then multiple linear regression of porosity and thickness together on UPF and comfort parameters were visually depicted by virtue of 3D linear plots. Residual analysis with quantile-quantile and probability plots, advocated the tests using the Shapiro-Wilk test. The result was validated by comparison with experimental data tested. The samples gave satisfactory relative errors and were supported by the z-test method. All tests indicated failure to reject the null hypothesis.

The predictive models were embedded into an interactive computer program. Fabric thickness and porosity are the inputs needed to run the program. It will predict the optimum UPF, areal density and thermophysiological comfort parameters. In a nutshell, knitters may use the program to determine optimum structural parameters for diverse permutations of UPF and thermophysiological comfort parameters; scilicet high UV protection together with low thermal insulation combined with low water-vapour resistance and high air permeability.

The purpose of this paper is to compare the bursting strength, bursting distension, air permeability and wale wise wicking rate properties of recycled polyester (r-PET) and virgin polyester (v-PET) raw materials from which single jersey knitted fabric samples are manufactured. Meanwhile, numerical optimization method was used in predetermined parameters to determine the optimum r-PET and v-PET blend ratio and yarn manufacturing technology. In the optimization analysis, the average values of the important yarn and fabric properties inspected were taken as a target according to the 50 percent proportion of r-PET and v-PET fiber for both compact and ring yarn manufacturing technology.

To encourage the use of value-added textile products produced from recycling PET bottle with the focus of social responsibility is a condition that should be evaluated within the scope of waste management. The recycling of PET bottles and finding new opportunities for the uses in different field are crucial for both contributing environmental economy and conserving natural energy resources. The most important alternative ways is to use the r-PET fiber from recycling PET bottle in textile industry. In this study, 19.7 tex r-PET/cotton and v-PET/cotton-blended compact and ring spun yarns were produced at different blending ratios at the same production parameters.

Results showed that blend type, blend ratio and yarn manufacturing technology have statistical significance effect on bursting strength and air permeability. Besides, it was found that blend type has no significance on wale wise wicking rate unlike other parameters. Optimization analysis indicated that single jersey knitted fabric with v-PET/CO 58.62/41.38 percent compact yarn had higher desirability with the value of 0.72.

At the present time, r-PET fiber is blended in small amount (approximately 5–15 percent blend ratio) with both cotton and polyester together. In addition, it is possible using different fiber blend types instead of cotton and polyester according to the usage area. The most important question is to determine the amount of r-PET proportion. In other words, both optimum yarn/fabric quality parameters should be ensured and at the same time life cycle of the apparels should not be short when the optimum r-PET proportion is taken into consideration.

Creases are marks that are created and left in a fabric during garment wear. Pressing is a process to flatten garment panels and sharpen garment edges and pleats. To minimize crease, the fabric should recover after pressing without creating a creased edge. Whereas, good pressing performance means the creased edge stays sharp after pressing. Good crease recovery and pressing performance appear contradictory. However, crease recovery and pressing performance are different as creases are formed during wear and pressing is carried out using pressing equipment such as iron, pressing machines, etc. The condition, i.e. temperature and humidity, under which the creases are formed in wear and pressing are very different. The latter has much higher temperature, pressure and humidity. This paper reports on an experimental investigation on the relationship between the crease recovery and pressing performance of wool and other fabrics. It was found that there are only generally weak to moderate relationships between the crease recovery as measured by the Shirley Crease Recovery Tester and the pressing performance as measured by the Siro‐Press Tester. The characteristics of wool fabrics, which have both good crease recovery and pressing performance, are identified. This study is a step towards fabric engineering.

Mercerization is one of the finishing treatments that often are used to improve the dye uptake properties and increase cotton fabrics' luster. Since comfort is a necessity of clothing and customers desire it more than ever, the finishing treatments that improve some properties of the fabric should not reduce clothing comfort. The aim of this paper was to investigate the effect of cold mercerization on the comfort properties of cotton fabrics.

A total of 15 woven fabric samples in different structures were randomly chosen. The samples were divided into two groups: the finished fabrics (i.e. those which were run through singing, desizing, and bleaching processes) and the mercerized fabrics (i.e. samples which underwent the singing, desizing, bleaching and mercerizing processes). The mechanical and thermo‐physiological comfort properties of these two groups were evaluated and results were compared.

The results showed that bending rigidity, shearing rigidity, air permeability, water vapour transmission and thermal resistance increased by cold mercerization. Moreover, frictional restraint, extensibility and wicking decreased. In other words, mercerization can improve some comfort properties of cotton fabrics and weaken the others.

The current literatures don't consider the effect of mercerization on the clothing comfort. The present work intends to evaluate the effect of cold mercerization on the mechanical (tactile) and thermo‐physiological comfort properties of cotton fabrics which are used as summer clothing.

One of the recent applications of fabrics is to use them for sound insulation. Accordingly, due to their low production cost and low relative density, fabrics have drawn attention in some of the industries such as the automotive and aircraft industries. The present study is aimed to investigate the effects of the fiber cross-section, porosity, thickness of samples and fuzzing of the knitted fabric on the sound absorption coefficient.

In the present study, fabrics with three different stitch densities were knitted by yarns consist of three different forms of fiber cross-section shapes (circular, elliptical and plus-shaped). In this work, the sound absorption coefficient of knitted fabrics was investigated with regard to the different fiber cross-sections and structural parameters using an impedance tube.

As indicated by the obtained results, the cross-section, porosity, thickness and mass per unit area of the fabrics were the determinant factors for the sound absorption coefficient. In addition to, the sound absorption coefficient and porosity were shown to have an inverse relationship.

A section of the present paper has been allocated to the investigation of the effect of the fiber cross-section and fuzzing of fabric on the sound absorption of plain knitted fabrics.

This paper aims to develop bilayer woven fabrics with different picking sequences with enhanced comfort without any change in the constituent materials.

Six bilayer woven fabrics were produced on Dobby loom with 3/1 twill weave using micro-polyester yarn. Three different picking sequences, i.e. single pick insertion (SPI), double pick insertion (DPI) and three pick insertion (3PI), were used in both face and back layers. The effect of picking sequence on air permeability (AP), volume porosity, thermal resistance and overall moisture management capability (OMMC) of the samples were analyzed.

The results showed that 3PI–3PI picking sequence gives the highest OMMC, AP and thermal resistance in bilayer woven fabrics and the least results exhibited by SPI–SPI picking sequence.

This research uses a bilayer woven system that develops channels and trapes the air causing higher thermal resistance; therefore, applicable for winter sports clothing rather than for summer wear. Developed bilayer woven fabrics can be used in winter sportswear to improve the comfort of the wearer and reduce fatigue during activity.

Authors have developed bilayer fabrics by changing the picking sequences, i.e. SPI, DPI and 3PI of weft yarns in both layers and compared their thermo-physiological comfort properties.