Comparison of regression and adaptive neuro-fuzzy models for predicting the compressed air consumption in air-jet weaving

The aim of this study was to compare the response surface regression and adaptive neuro-fuzzy models for predicting the compressed air consumption in air jet weaving. The prediction models are based on the experimental data of 100 samples comprising weft yarn count, fabric width, loom speed and reed count as input variables and compressed air consumption as output/response variable. The models quantitatively characterize the linear and quadratic relationships as well as interactions between the input and output variables exhibiting very good prediction ability and accuracy, with ANFIS model being slightly better in performance than the regression model. The models could be used for estimating the compressed air consumption, identifying air leakages and production planning in a weaving mill.     

Dimensional and physical properties of plain knitted fabrics made from 50/50 bamboo/cotton blended yarns

In this study, the dimensional and some physical properties of plain knitted fabrics made from 50/50 bamboo/cotton blended yarns are investigated. In order to see the differences and similarities, the results are then compared with those for similar fabrics knitted from 50/50 conventional viscose/cotton and 50/50 modal/cotton blended yarns. Each fabric type was produced with three different stitch lengths. After all fabrics were dyed under identical dyeing conditions, they were subjected to dry and full relaxation treatments. For dimensional properties of fabrics, course, wale and stitch densities were measured. Then, by calculating statistically best-fit lines passing both through the experimental points and the origin, dimensional constants i.e. k values were predicted in terms of the fiber types. The result show that each fabric type knitted from bamboo/cotton, viscose/cotton and modal/cotton blended yarns behaves in a similar manner. However, in both dry and fully relaxed states, the modal/cotton knitted fabrics tend to have slightly higher k values than the bamboo/cotton and viscose/cotton knitted fabrics. For physical properties, fabric weight per unit area, thickness, bursting strength, air permeability and pilling were evaluated. The results show that the weight, thickness and air permeability values are independent of the fiber type. Plain knitted fabrics from modal/cotton blended yarns have the highest bursting strength values. Plain knitted fabrics from bamboo/cotton blended yarns tend to pill less.     

Comparison of the new methodologies for predicting the CSP strength of rotor yarn

This paper provides preliminary results on the relative performance of the adaptive neuro-fuzzy system inference (ANFIS) model versus linear multiple regression method, when applied to the use of cotton fiber properties to predict spun yarn strength obtained from open-end rotor spinning. Fiber properties and yarn count are used as inputs to train the two models and the output (dependent variable) would be the count-strength-product (CSP) of the yarn. The predictive performances of the two models are estimated and compared. We found that the ANFIS has a better average prediction successful in comparison with linear multiple regression model.     

Predicting properties of single jersey fabrics using regression and artificial neural network models

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 (α _e 3.8, α _e 4.2, and α _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.     

Dimensional,physical and thermal comfort properties of plain knitted fabrics made from modal viscose yarns having microfibers and conventional fibers

The dimensional, some physical and thermal comfort properties of the plain knitted fabrics having modal viscose microfibers in three different stitch lengths are investigated in comparison with the similar fabrics having conventional modal viscose fibers. The fabrics made from microfibers and conventional fibers exhibit different dimensional properties. The stitch density results and the dimensional constants calculated at the fully relaxed state reveal that the fabrics with microfibers tend to have lower shrinkage tendency than those with conventional fibers. The statistical results show that the fiber type (or fiber fineness) and the stitch length affect the some physical properties and all of the thermal comfort properties of the fabrics significantly. The bursting strength values of the fabrics with microfibers are observed to be slightly higher than those of the fabrics with conventional fibers. However, the difference between the bursting strength values of these fabrics is found to be statistically unimportant. The fabrics with microfibers reveal lower thickness and air permeability and, higher pilling tendency than those with conventional fibers. It is also observed from the thermal comfort results that the fabrics made from microfibers have higher thermal conductivity, thermal absorptivity and maximum heat flux values and, lower thermal resistance and thermal diffusivity values. Because of the higher thermal absorptivity and maximum heat flux values, the fabrics from microfibers provide cooler feeling when compared with those from conventional fibers.     

Effect of polypropylene fiber cross sectional shapes on some structural/mechanical fiber properties and compressibility behaviour of plain knitted fabrics

Synthetic fibers are generally produced with circular cross sectional shapes. Other cross sectional shaped fibers such as trilobal, triangular, hollow and pentagonal fibers are also produced to improve some properties of fibers and fabrics such as lustre, handle, wicking rate, strength, stiffness and bulkiness. In this research we aimed to investigate compressional behaviours of fabrics knitted from polypropylene fibers having three different cross sectional shapes; namely circular, trilobal and triangular. Morphological, structural and mechanical properties of produced fibers were evaluated by using scanning electron microscopy, X-ray diffractometry, differential scanning calorimetry and tensile tester, respectively. In terms of structural and mechanical properties, no significant differences were found related to fiber cross sectional shapes. Then, plain knitted farbrics were produced and compressional properties of these fabrics were investigated. Fabrics knitted from trilobal fibers showed the highest compressibility properties and it is followed by fabrics which are produced from triangular and circular fibers.     

The mechanical properties and abrasion behavior of warp knitted fabrics for footwear

The abrasion behavior of three kinds of warp knitted fabrics, which are normally used for upper sole of footwear, was evaluated. We measured the changes of mechanical and structural properties of each sample as abrasion cycle increased. Each sample showed similar trends in compression and surface properties but there were significant differences in abrasion rate among the samples. The mechanical properties showed remarkable differences with directions. The frictional coefficient (MIU) of fabric surface increased at the beginning of abrasion and decreased as abrasion cycles increased. The weight and thickness of the fabric linearly decreased with abrasion cycles. The surface roughness (SMD) and the compressional resilience (RC) decreased as abrasion cycles increased while compressional energy (WC) increased.     

Prediction of rotor spun yarn strength from cotton fiber properties using adaptive neuro-fuzzy inference system method

In this study, we present the application of a hybrid neuro-fuzzy system for the prediction of cotton rotor spun yarn strength from cotton fiber properties. The proposed system possesses the advantages of both artificial neural networks and fuzzy logic, and is thus more intelligent. HVI (high volume instrument) and Uster AFIS (advanced fiber information system) fiber test results are used to train the neuro-fuzzy inference system. We also study the degree of impact of each fiber property on the rotor spun yarn strength. Fiber strength, upper half mean length, length uniformity and yarn count have a positive impact whereas micronaire, yellowness and short fiber content have a negative impact on rotor spun yarn strength.     

Investigation on air permeability of finished stretch plain knitted fabrics. I. Predicting air permeability using artificial neural networks

Air permeability is one of the most important utility properties of textile materials as it influences air flow through textile material. Air permeability plays a significant role in well-being due to its influence on physiological comfort. The air permeability of textile materials depends on their porosity. There are a lot of structural properties of textile materials also operating parameters (knitting+finishing) influencing air permeability and there are also statistically significant interactions between the main factors influencing the air permeability of knitted fabrics made from pure yarn cotton (cellulose) and viscose (regenerated cellulose) fibers and plated knitted with elasthane (Lycra) fibers. Two types of artificial neural networks (ANNs) model have been set up before modeling procedure by utilizing multilayer feed forward neural networks, which take into account the generality and the specificity of the product families respectively. A virtual leave one out approach dealing with over fitting phenomenon and allowing the selection of the optimal neural network architecture was used. Moreover this study exhibited that air permeability could be predicted with high accuracy for stretch plain knitted fabrics treated with different finishing processes. Within the framework of the work presented, ANNs were applied to help industry to adjust the operating parameter before the actual manufacturing to reach the desired air permeability and satisfy their consumers.     

Comparison of degree-day distribution models for predicting emergence of the cabbage aphid on canola

Cabbage aphid, Brevicoryne brassicae (L.), is a serious pest on canola, Brassica napus L. Estimation of required degree-days for 50% emergence of the population is of special interest for controlling this aphid. To precisely predict 50% emergence of aphid populations as a function of accumulated degree-days, eight distribution models were tested. Models were evaluated statistically and validated with a separate data set collected from three canola fields. Observed cumulative emergence of the aphid was well described by three models. The sigmoid model proposed by Brown and Mayer was recommended to describe 50% emergence of the cabbage aphid population, because the model is simple and the parameter b denotes the accumulated degree-days at 50% emergence. The selected model could be used to better time insecticide applications and to more efficiently forecast aphids in canola fields.     

Effects of softeners and laundering on the handle of knitted PLA filament fabrics

We have studied the effects of softeners and repeated laundering on the handle of knitted fabrics constructed from poly(lactic acid) (PLA) filament yarns derived from corn-starch. The fabrics were assessed: a) subjectively, via a panel of volunteers, in terms of their perceived softness and ‘scroopiness’; and b) objectively, using a Kawabata Evaluation System for Fabrics (KES-F), in terms of their low-stress mechanical properties. The study employed two fabric variants and a range of commercial softeners in an attempt to determine the combination that would provide optimal handle and durability to laundering. We found the standard KES-F parameters B, 2HB, G, 2HG, and SMD to be generally well-correlated with the subjective assessment of softness and scroopiness. Although repeated laundering reduced somewhat the beneficial effects of the softeners, this deterioration was not severe, and we were able to identify specific formulations that can provide good handle coupled with acceptable durability. The fabric handle was seen to be influenced by the chemical nature of the softening agent, the type of emulsion employed and the degree of hydrophobicity (assessed in terms of wettability); on the other hand, the ionicity of the softener appeared not to play a significant role.     

Effect of filament size on the water transport of weft and warp knitted fabrics

Warp and weft knitted fabrics comprising polyethylene terephthalate/Co-PET sea-island bicomponent fibers were fabricated in this study. The knitted fabrics were treated in alkali solution to develop knitted fabrics composed of nano-scale filaments. The structural change and water transport behavior of the alkali-treated knitted fabrics were then compared. Results revealed that the filament diameters decreased from 20 µm to 850 nm after alkali treatment. The porosities of warp and weft knitted fabrics decreased by 4.8 % and 10.1 %, respectively, whereas their area densities increased by 68.8 % and 67.2 %, respectively. The wicking height and wicking rate of both types of fabric composed of microfilaments increased with prolonged alkali-treatment time. However, the water absorption properties such as absorption capacity and absorption rate of the knitted fabrics composed of nano-scale filaments significantly increased because of their low porosity and high area density.     

Comparative study on the characteristics of knitted fabrics made of vortex-spun viscose yarns

Murata vortex spinning system is based on the air jet spinning system. The vast majority of previous works deal with the properties of vortex spun (VS) yarn and the spinning system. In this study, we investigated knitted fabrics from VS yarn in comparison with fabrics from ring (RS), compact (CS) and open-end rotor (OES) spun yarns made from viscose. The effect of yarn spinning system on dimensional and physical properties of knitted fabrics was explained with specific attention to fabrics from VS yarn. Shrinkage of fabrics from VS yarn has the lowest at widthwise direction, while having the highest at lengthwise direction. It is shown that the order of fabric spirality and twist liveliness for yarns from different spinning systems are quite similar. However, relation between loop shape factor and angle of spirality is inconsistent. Angle of spirality of fabrics from VS yarn is higher than fabrics from OES yarn, but lower than that of others. The bursting strength of fabrics from VS yarn is lower than that of those from RS and CS yarns and higher than that of those from OES yarn. From this study, it is also evident that fabrics from VS yarn have the lowest pilling tendency and highest resistance to abrasion.     

Dimensional,physical and thermal properties of plain knitted fabrics made from 50/50 blend of modal viscose fiber in microfiber form with cotton fiber

In this study, the dimensional, physical and thermal comfort properties of the plain knitted fabrics made from 50/50 blend of modal viscose fiber in microfiber form with cotton fiber are compared with those of the similar fabrics made from 50/50 blend of conventional modal viscose fiber with cotton fiber and made from 100 % cotton fiber. All the fabric types are produced in three different stitch lengths. The slight differences among the fabric types are observed in terms of the stitch density results and the dimensional constants calculated in the fully relaxed state. In the fully relaxed state, the dimensional K values of the modal microfiber blended knitted fabrics are found to be more closely resemble those of the cotton fabrics rather than those of the conventional modal fiber blended fabrics. The lowest fabric thickness and bursting strength results are obtained for the modal microfiber blended fabrics. The modal microfiber blended fabrics reveal lower air permeability than the conventional modal fiber blended fabrics and higher air permeability than the cotton fabrics. It is also observed from the thermal comfort results that the modal microfiber blended fabrics have the lowest thermal resistance and the highest thermal absoptivity values. The thermal conductivity results of the modal microfiber blended fabrics are lower than those of the cotton fabrics and higher than those of the conventional modal fiber blended fabrics. Because of the highest thermal absorptivity values, the modal microfiber blended fabrics provide the coolest feeling when compared with the other two fabric types.     

Estimation on the 3D porosity of plain knitted fabric under uniaxial extension

In this article we study the 3D porosity of plain weft knitted fabric while is subjected to extension under different uniaxial extension in course direction. There are a few models for 3D porosity investigation of weft knitted fabrics such as Benltoufa model and Karaguzel model as theoretical models and empirical Guidoin model. To investigate the accuracy of these models, plain knitted fabrics were produced over a different range of knitting stiffness. Thereafter, the estimated porosities of the fabrics using the theoretical models were compared with the experimental values which are obtained from Guidoin empirical model. It was concluded that Karaguzel model shows reliable and trustful result while, Benltoufa model shows huge differences in comparison with Guidoin model. In order to reduce these differences, an improved model which is named as i-model is introduced.     

The influence of corona discharge treatment on the properties of cotton and polyester-cotton knitted fabrics

In this study, the effect of corona discharge treatment on the physical and mechanical properties of bleached cotton and polyester-cotton fabrics were investigated. For this purpose, the samples were treated by corona discharge at two levels of voltage 5 and 10 kV, and at various duration times of plasma, ca. 1.4, 2.1 and 3.5 min. The corona discharge treatment was applied on the fabric samples before and after bleaching treatment. The results show that the corona influences on the surface morphology, breaking strength, air permeability, abrasion resistance, and pilling of cotton and polyester-cotton fabrics. Moreover, the levels of voltage and duration of plasma have a different effect on the properties of fabrics.     

The effects of wool surface characteristic on fuzzing and pilling of knitted fabrics

The fuzzing and pilling of untreated, chlorinated and oxidized wool knitted fabrics were compared with frictional coefficients measured by capstan method, surface modification observed by scanning electron microscopy (SEM), the surface roughness and the scale height assessed by atomic force microscopy (AFM), and hairiness imaged on the three-dimensional rotational microscopy. The pilling comparative experiments of the corresponding knitted fabrics were conducted by means of Pillbox method. Experimental results showed that some scales on the oxidized fiber surface were partially cleaved and some grooves generated. With oxidization treatment, the anti- and with-scale of friction coefficient increase with decreasing the thickness of scales and the yarn hairiness. There is good correlation between the result of AFM and the change in frictional coefficients. The pilling grade of knitted fabric comprised of oxidization wool is 2.5, and the average numbers of pills per 25 cm² is 25. It is postulated that the surface topography, the frictional properties of oxidized wool fibers and surface hairs of corresponding yarns may limit the ability of those surface fibers to form fuzz and of those fuzz for pill formation.     

Compression properties of weft knitted fabrics consisting of shrinkable and non-shrinkable acrylic fibers

High-bulk worsted yarns with different shrinkable and non-shrinkable acrylic fibers blend ratios are produced and then single jersey weft knitted fabrics with three different structures and loop lengths are constructed. The physical properties of produced yarns and compression properties of produced fabrics at eight pressure values (50, 100, 200, 500, 1000, 1500 and 2000 g/cm²) were measured using a conventional fabric thickness tester. Then, weft-knitted fabric compression behavior was analyzed using a two parameters model. It is found that at 40% shrinkable fibre blending ratio the maximum yarn bulk, shrinkage, abrasion resistance and minimum yarn strength are obtained. It is also shown that high-bulk acrylic yarn has the highest elongation at 20% shrinkable fibre blend ratio. The statistical regression analysis revealed that the compression behavior of acrylic weft-knitted fabrics is highly closed to two parameter model proposed for woven fabrics. It is also shown that for weft-knitted structure, there is an incompressible layer (V′) which resists against high compression load. Acrylic weft-knitted fabrics with knit-tuck structure exhibit higher compression rigidity and lower softness than the plain and knitmiss structures. In addition, at 20% shrinkable fibre blend ratio, the high-bulk acrylic weft-knitted fabrics are highly compressible.     

Selection of yarn for the predefined tensile strength of cotton woven fabrics

In order to meet the required strength of a fabric, selection of yarn is difficult because tensile strength of woven fabric depends upon a number of factors. Still, the manufacturers have to use hit and trial method in order to select the yarn for the required tensile strength of fabric. This study was carried out to develop regression equations for the prediction of yarn tensile strength suitable for the predefined strength of cotton woven fabrics. These equations were developed by using empirical data obtained from two hundred and thirty four fabric samples prepared under a systematic plan with different constructions. Prediction proficiency and precision of these regression equations were evaluated by correlation analysis of the predicted and actual warp and weft yarn strength values of another set of thirty six fabric samples. The results show a very strong prediction precision of the equations.     

A study on the structural properties of plain fabrics using the lenticular model

The structural properties of a plain fabric were considered using the lenticular model. The structure of a plain woven fabric can be defined in terms of warp yarn number, weft yarn number, warp fabric density, weft fabric density, warp crimp, and weft crimp. Many structural variables of the plain fabric could be calculated by the lenticular model using these terms. Also, this model can be used to explain the geometry of the flattened yarns that occur during the weaving process. Flattening factors of threads for various types of fibers were calculated, compared, and explained with the number of yarn twist. Flattening factors were found to affect the structural variables of the fabric such as fabric thickness, air permeability, and yarn crimp. Yarn crimp was also studied with variation of the structural variables of the fabric.