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The objective of this study is to examine mechanical performance of double-layered woven fabrics used in car seat upholstery. For this purpose, 450 denier polyester yarns were supplied to produce double-layered woven fabrics. For the production of the fabrics, full weft connection, which is warp yarn of the top layer makes a connection with the weft yarn of the bottom layer, was used. To produce such a fabric, four different factors such as bottom layer pattern, number of interlacing warps in a unit report, number of interlacing picks per top warp and number of weft skips were investigated using Taguchi experimental design. After weaving stage, fabrics were stentered. Mechanical and physical properties of the fabrics were measured before and after stentering and the results were analysed with regard to Taguchi experimental analysis.

The study aims to investigate the effect of hollow yarn structure and the sheath-core proportion of hollow yarns on the permeability properties of the knitted fabrics. In order to accomplish this, core yarns in the yarn count of 59 tex were produced by using cotton, viscose, wool, and polyester fibers in the sheath and different ratios of polyvinyl alcohol (PVA) in the core. After completion of yarn production on ring spinning frame, the yarns in the form of packages were used to produce plain knitted fabrics. Fabrics were then divided into two groups, one of which was washed during a time period in order to remove PVA from the core to obtain hollow yarn structure. Air and water permeability, and wicking properties of the knitted fabrics were measured before and after washing processes. Mechanical properties such as pilling and bursting strength of the fabrics were also examined. The results show that washing process and PVA proportion used to produce core spun yarns have a significant effect on t...

In the scope of this study, core yarns in the yarn count of 59 tex were produced by using cotton, viscose, wool, and polyester fibers in the sheath and different ratios of polyvinyl alcohol (PVA) in the core. After completion of yarn production on ring spinning frame, winding process was performed in order to get packages. These yarns in the form of packages were washed during a time period in order to remove PVA from the yarn structures to obtain hollow yarn structure. Yarn irregularity and yarn tensile tests were performed in the form of packages before and after washing process. As a result of these tests; it was observed that values of yarn unevenness and tensile tests were significantly influenced by the core-sheath proportion and washing process.

When literature is reviewed in detail, it can be seen that there is limited research, especially on Angora rabbit fiber and again in none of the research was the felting propensity of luxury protein fibers from different origins (goat, camelid and rabbit) related with fiber properties, such as cuticle scale frequency and scale height. For this purpose, hair-based luxury fibers, which are most widely used and consumed all over the world (cashmere, mohair, angora, Huacaya alpaca and Suri alpaca) were chosen in order to measure fiber diameter, fiber length, cuticle scale frequency and scale height of these fibers. As a result, detailed relations about the felting propensity of the hair-based luxury fibers with the fiber properties were investigated. According to the experimental analysis, it was determined that angora, which is the finest and the shortest animal fiber, showed the lowest felting propensity. On the other hand, Suri alpaca fiber with a low scale height gave the highest feltability due to being the longest among the investigated fibers.

WOS: 000407965200015, In this work effect of using hollow yarns on the permeability properties of the single jersey knitted fabrics were studied. Firstly yarns were produced by ring spinning machine using cotton, viscose and acrylic fibres in the mantle and water soluble polyvinyl alcohol (PVA) fibre in the core. Single jersey fabrics were knitted and PVA core was removed subsequently by washing process to create hollow yarn. Weight, air permeability and water transmission rate properties of fabrics were measured before and after washing and compared with reference fabrics. Due to the removal of PVA fibres from the yarn core after washing treatment, air permeability and water vapour transmission rate of the all kind of single jersey fabrics which were produced with hollow yarns increased as well as weight of the fabrics decreased which will cause more comfort during any exercise. It was also found that mantle fibre type and PVA ratio have significant effect on the fabric properties., Namik Kemal University [NKUBAP.00.17.AR.13.02], This work was financially supported by the Namik Kemal University [project number NKUBAP.00.17.AR.13.02].

In this study, in order to produce different water-oil repellent and wrinkle resistant fabrics, 21 different kinds of blended woven fabrics were treated (padded and transfered) with both classic and nano chemicals according to 4 different levels of concentrations. Afterwards, water, oil repellency and wrinkle angle recovery properties of the fabrics were measured. The purpose of this study is to predict these aforementioned functional properties of the fabrics before manufacturing based on the fabric blend, treatment method, used chemicals and chemical concentrations with the help of multi layer perceptron, one of the most popular network architecture. As a result of the study, it can be concluded that multi layer perceptron method can also be used for the classification problems successfully.

In this study, in order to observe the effect of spinning systems such as ring, rotor and vortex, and twist direction of the folded yarns on the fabric handle properties, single end yarns were produced in the same yarn count, yarn twist, and twist directions. After that, the single end yarns were folded on the same doubling machine in two twist directions of S and Z. These folded yarns were used as weft yarns in the woven fabrics. In addition to these parameters, four different weft insertion orders were tried (SSSS, ZZZZ, SSZZ, SZSZ) to be observed whether the insertion order makes any difference in the handle values of the fabrics. It was concluded from the study that handle properties of the fabrics produced with ring folded yarns are better than the ones produced with rotor and vortex folded yarns regardless of the weft insertion order. The fabrics produced with SSSS weft insertion order are the softest among all fabrics in all spinning systems. Besides, using the weft insertion order of SZSZ makes the fabric softer than SSZZ.

The objective of the second part of the study is to investigate the retained spliced diameter with regard to splicing parameters and fiber and yarn properties. In order to analyze the effects of the fiber and yarn properties on the retained spliced diameter of ring spun cotton yarns, the yarns were produced from eight different cotton types in three yarn counts (29.5, 19.7 and 14.8 tex) and three different twist coefficients (αtex 3653, α tex 4038, αtex 4423). To investigate the effects of splicing parameters on the retained spliced diameter, opening air pressure, splicing air pressure and splicing air time were set according to an orthogonal experimental design. The retained spliced diameter was calculated and predicted by using an artificial neural network (ANN) and response surface methods. Analyses showed that ANN models are more powerful compared with response surface models in predicting the retained spliced diameter of ring spun cotton yarns.

In this study, the effects of splicing parameters, fiber and yarn properties on the tenacity and elongation of spliced yarns were investigated in detail. For this purpose, yarns from eight different cotton types, having three different counts (29.5, 19.7 and 14.8 tex) and three different twist coefficients (α tex 3653, αtex 4038, αtex 4423) were produced. Fiber properties measured using an Advanced Fiber Information System fiber tester were evaluated. Artificial neural network and response surface models were used to analyze spliced yarn tenacity and elongation as dependent variables. As independent variables, fiber properties together with the machine settings such as opening air, splicing air and splicing time, yarn twist and yarn count were chosen. As a result of the study, equations and neural network models that predict the tenacity and elongation of the spliced yarns were obtained. The obtained equations and models are statistically important and have high coefficient of multiple determination ( R2).

With the increasing demand of fabrics for special usage areas, more complex woven structures are designed and from the structural point of view, especially the parameters which affect the comfort properties become more important. This paper reports the effect of structural parameters of double layered woven fabrics, such as number of interlacing picks, period of interlacing and number of weft skips on the basic comfort properties of the fabrics (thickness, air permeability and wicking properties) produced according to Taguchi orthogonal array design. The investigated parameters were determined before and after finishing treatment. According to the results, it is found that period of interlacing has an important effect on the thickness and air permeability of both untreated and treated fabrics whereas in terms of drying coefficient, the effect of the investigated parameters is not statistically important.

WOS: 000300550300013, In our previous works, we had predicted cotton ring yarn properties from the fiber properties successfully by regression and ANN models. In this study both regression and artificial neural network has been applied for the prediction of the bursting strength and air permeability of single jersey knitted fabrics. Fiber properties measured by HVI instrument and yarn properties were selected as independent variables together with wales' and courses' number per square centimeter. Firstly conventional ring yarns were produced from six different types of cotton in four different yarn counts (Ne 20, Ne 25, Ne 30, and Ne 35) and three different twist multipliers (alpha (e) 3.8, alpha (e) 4.2, and alpha (e) 4.6). All the yarns were knitted by laboratory circular knitting machine. Regression and ANN models were developed to predict the fabric properties. It was found that all models can be used to predict the single jersey fabric properties successfully. However, ANN models exhibit higher predictive power than the regression models.