Bagging Behavior Research Articles

Contribution on Modeling of Bagged Denim Fabric Behavior After Mixed Washing Using PCA and Regression Techniques

ABSTRACT This study evaluates the effect of mixed washing treatment on the bagging behavior of denim fabrics. Six types of denim fabrics were washed under different conditions. Then, the bagging test was applied. Furthermore, the most influential factors of this treatment on the bagging ability of denim fabric were discussed using the main effect plots. This method shows that the quantity of pumice stone, the quantity of enzyme and the fabric are the most influencing factors. The increase in the amount of enzyme or pumice stone increases the occurrence of the bagging problem. Since the fabric is the dominant factor for all bagging properties, the characterization with Kawabata instruments of treated and untreated fabrics was performed. Then, we used the principal component analysis method to select the most important parameters. A reduction of 52.78% in parameters was achieved. Finally, the linear regression models were obtained to predict the bagging properties. The regression coefficients (R2) range between 96.85% and 99.43% and the adjusted R2 is between 92.34% and 98.13%, which confirms the efficiency of our models. These models are crucial for the manufacturers of washing denim since they could help the industrials to predict denim fabric’s bagging behavior after mixed washing.

Effect of Desizing Treatment on the Bagging Behavior of Denim Fabrics

This research aims to study the impact of desizing treatment on the bagging behavior of denim garments. Therefore, six denim fabrics with the same weaves and different characteristics were desized under different conditions. Then, the bagging behavior properties of the treated and untreated denim fabric were analyzed and investigated. Thanks to analysis of variance and the main effects plots, the influencing factors were found. The obtained results showed that the most important factors are the characteristics of the samples like the percentage of elastane and polyester fibers, and weight. In addition, it can be concluded that the concentration of desizing agents affects widely the bagging fatigue percentage.

Effect of washing treatment on residual bagging height of denim fabrics

The effect of various washing processes carried out under industrial conditions on the bagging properties of denim fabrics has been studied in order to understand why residual bagging height behavior remains after garment uses due to internal stress, shrinkage, and excessive extensions. Three different washes have been used for denim samples, already dyed with vat indigo. To evaluate the washing treatment contributions to the bagging behaviors of all studied samples, the residual bagging height characteristic is investigated. It is studied before and after each washing treatment (desizing, enzyme washing, and bleaching). The results show that the residual bagging height increases after all types of washing treatments except for the bleaching ones. Nevertheless, the washed elastomeric denim fabrics (within elastane filament percentages) present significant recovery rates of bagged fabrics after all applied washes. By comparing the results obtained in this study, it may be concluded that the applied enzymatic washing process affects more the bagging behavior of denim fabrics than those of the desizing and bleaching treatments.

Study of the effect of enzymatic washing parameters on the bagging properties of denim fabric with Taguchi method

AbstractThis study aims to evaluate the effect of neutral enzyme washing on the bagging behavior of denim garments and optimize the conditions of this treatment using the Taguchi design. Six types of fabrics were selected with the same weaves and different characteristics. These samples were washed with a neutral cellulase enzyme under different conditions such as enzyme concentration (0.3%, 2%, and 4%), temperature (30, 45, and 65°C), time (15, 45, 75 min), and material to liquor ratio (1:5, 1:8, and 1:10). To evaluate the effect of enzymatic washing on the bagging behavior, we investigated the residual bagging height, the bagging fatigue percentage, the bagging resistance, and the bagging recovery percentage. Thanks to the main effects plots the influencing factors were obtained and using the signal‐to‐noise ratio diagram, the optimum conditions were determined. The obtained results showed that these bagging properties were affected by the washing conditions and that the most important factors are the characteristics of the samples such as the percentage of elastane and polyester fibers, weight and weft density, and enzyme concentration. The process parameters were optimized and the optimized washing conditions for the best value were 0.3% enzyme concentration at 45°C for 75 min, in material to liquor ratio of 1:8. Concerning the factor of the sample, the results show that the increase of the percentage of elastane or polyester fibers in the composition of denim fabric decreases the problem of deformation and bagging. Therefore it is recommended to add a percentage of these fibers in the construction of the denim to improve the bagging recovery. Thus, the increase in the weft density minimizes that bagging phenomen appears.

Investigation into evaluation of wearing bagging behavior for woven garments

Garment bagging is the plastic deformation of the knee, elbow and other parts of the garment when the human body moves. The current methods and indexes for evaluating the bagging performance of woven garments are not comprehensive enough. In view of this situation, 16 pieces of fabrics were made into pants-tube for actual wearing and bagging. The camera and the 3D laser scanner were used to acquire images and point cloud data of garments respectively. Then feature extraction was performed on the processed data to get two traditional geometric quantization indexes, bagging height and bagging volume. Furthermore, two new geometric quantification indexes were proposed: warp and weft maximum bagging rate. And several kinds of surface quantization indexes were also could be extracted, namely mean, average deviation, roughness, variance and torsion. At the same time, the subjective evaluation results had been obtained by the bagging images and the bagging 3D curved surfaces. After that, correlation analysis and ridge regression analysis were carried out between the two groups of indexes and the subjective score results. The results showed that, the two new geometric quantitative indexes were highly correlated with the subjective score, and the correlation coefficient were −0.883 and −0.923, respectively. The surface quantization indexes regression equation and the geometric quantification index regression equation were both accurate in predicting the subjective score, and the adjusted R2 reached 92.7% and 91.3%. The 3D laser scanning technology could be used to evaluate the garment bagging accurately.

Effect of Stone Washing Parameters on Denim Behavior Bagging

ABSTRACT This research investigates the impact of stone washing treatment on denim fabrics. Garments were washed at different conditions, and then the bagging behavior properties and the mechanical properties using the Kawabata evaluation system KES-FB of the treated and untreated denim fabric were analyzed and investigated. Furthermore, to predict the appearance and the bagging ability of denim fabric, the significant contribution of the inputs/outputs parameters on the bagging behavior is discussed using the principal component analysis (PCA) technique. Thanks to this method, the numbers of the influent parameters were reduced at a percentage of 45.71%. The results show the accuracy of the linear regression method to predict the bagging behavior in the experimental design of interest. Moreover, the R2 ranged from 83.6% to 92.7%, traduces that the obtained models seem effective and can help industrials to explain the effect of washing treatment in the bagging behavior of denim fabric.

Strength, fatigue and bagging properties of plated plain knitted fabrics containing different rates of elastane

Purpose Elastane yarns contribute significant elastic properties to all types of fabrics and these properties for very important for wears including tights, sportswear, under wear, casual wear, swimwear, corsetry, etc. in terms of appearance, comfort and duration of wear. The paper aims to discuss this issue. Design/methodology/approach It is investigated with this study strength, fatigue and bagging properties of plated plain knitted fabrics containing different rates of elastane. Findings The study showed that single jersey, not having elastane and having the lowest fabric tightness, has the lowest bursting strength, the highest fatigue loading values in high extensions, the lowest fatigue height values and the worst bagging behavior. On the contrary of single jersey, full elastane fabric has the exact opposite characteristics considering the fabric properties examined. Originality/value Fabric with 1×1 elastane and fabric with 2×1 elastane is similar, and these fabrics show bagging behavior better than single jersey and worse than full elastane fabric whereas the other properties of these fabrics are close to full elastane fabric.

Performance of Porous Pavement Containing Different Types of Pozzolans

Underlying fabrics can change the appearance, function and quality of the garment, and also add so much longevity of the garment. Nowadays, with the increasing use of various types of fabrics in the garment industry, their resistance to bagging is of great importance with the aim of determining the effectiveness of textiles under various forces. The current paper investigated the effect of underlying on the bagging behavior of denim fabrics. The experiments carried out on four different denim fabrics as the main components including cotton, polyester and lycra, as well as three types of adhesive interlining and three common lining as the underlying components. The adhesive interlining was added to the fabric by using a fusing machine, and the lining was sewn to the fabric. The bagging behavior was assessed by extraction of the residual bagging height using the image processing method and the bagging fatigue percentage by stress-strain diagram. The results showed that with the addition of adhesive interlining and lining to the fabric, the bagging fatigue percentage increased. The lining sewn to the fabric reduced the residual bagging height. Also, the friction between the face fabric and the lining was an important factor that, the bagging fatigue percentage increased with increasing the friction, regardless of the fabric material.

Investigating the Effect of Underlying Fabric on the Bagging Behaviour of Denim Fabrics

Underlying fabrics can change the appearance, function and quality of the garment, and also add so much longevity of the garment. Nowadays, with the increasing use of various types of fabrics in the garment industry, their resistance to bagging is of great importance with the aim of determining the effectiveness of textiles under various forces. The current paper investigated the effect of underlying on the bagging behavior of denim fabrics. The experiments carried out on four different denim fabrics as the main components including cotton, polyester and lycra, as well as three types of adhesive interlining and three common lining as the underlying components. The adhesive interlining was added to the fabric by using a fusing machine, and the lining was sewn to the fabric. The bagging behavior was assessed by extraction of the residual bagging height using the image processing method and the bagging fatigue percentage by stress-strain diagram. The results showed that with the addition of adhesive interlining and lining to the fabric, the bagging fatigue percentage increased. The lining sewn to the fabric reduced the residual bagging height. Also, the friction between the face fabric and the lining was an important factor that, the bagging fatigue percentage increased with increasing the friction, regardless of the fabric material.

Modeling the bagging behavior of worsted fabrics using response surface methodology

In this paper, we have studied the effect of a number of loading cycles on fabrics bagging behavior, and then investigated the influence of factors such as sample weight, test speed, and sphere diameter on the worsted fabrics bagging behavior using response surface method (RSM). Six worsted fabric types with different weights were prepared and then the bagging properties of these fabrics were measured using a newly developed test method. Bagging parameters including bagging force, work, fatigue, resistance, hysteresis, and residual height are calculated. Then, a statistical model (RSM) was used for the experimental plan (with these factors) to determine the runs of an experiment (or selected points). The experimental results showed that sample weight and sphere diameter have a significant effect while test speed has no significant effect on the bagging parameters. Also, the fitted models of bagging parameters are obtained and coefficient effects are estimated.

Analytical studies on woven fabrics’ bagging performance affected by the material, yarn, and fabric parameters

The present work focuses on investigating the bagging behavior of woven fabrics produced from viscose and polyester/viscose yarns. In this paper, the bagging deformation – in terms of different bagging parameters (bagging resistance, bagging fatigue, bagging hysteresis, and residual bagging hysteresis) – has been interpreted by fabric’s physical and mechanical properties which were obtained from FAST system. The statistical analysis revealed that there is a significant correlation between the bagging parameters. Also, it was concluded that the samples’ physical and mechanical properties correlate significantly with bagging parameters. Additionally, the effects of four different variables such as material type, spinning system, weave pattern, and weft density on bagging parameters have been studied. Considering the high correlations between all the bagging parameters, it was decided to analyze only the parameter bagging fatigue in this paper. The results showed that all the fabric variables except the parameter weft density have significant effects on bagging fatigue performance.

Prediction of Fabric Bagging Occurred by an Artificial Arm Under Dynamic Conditions

In recent research, the bagging behaviour of fabrics occurred during the cyclic motions of an arm were investigated experimentally by using a set of woven fabrics. The new testing instrument similar to an arm and having an elbow joint was used and test fabrics were deformed under dynamic conditions. 22 suiting fabrics were used as test fabrics composed of 100% cotton and cotton blend, 100% wool and wool blend, 100% linen and 100% polyester fiber as raw material. Besides fabric bagging tests, fabric structural properties, tensile and bending properties were determined in the context of the study. All objective data were used to predict fabric bagging parameters. Regression analyses were performed by multiple linear regression models to predict residual bagging height.

Study of the influential inputs on the bagged denim fabric behaviors using the principal component analysis method

Purpose – The purpose of this paper is to predict the appearance of denim fabric after repetitive uses judging the denim cloth behavior and performance in viewpoint of bagging ability. Hence, it attempts to carry out the significant inputs and outputs that have an influence on the bagging behaviors using the Principal Component Analysis (PCA) technique. In this study, the Kawabata Evaluation System parameters such as the frictional characteristics, the bending, compression, tensile and shear parameters are investigated to propose a model highlighting and explaining their impacts on the different bagging properties. To improve the obtained results, the selected significant inputs are also analyzed within their bagging properties using Taguchi experimental design. The linear regressive models prove the effectiveness of the PCA method and the obtained findings. Design/methodology/approach – To investigate the mechanical properties and their contributions on the bagging characteristics, some denim fabrics wer...

Optimization of bagged denim fabric behaviors using the genetic algorithms and the ant colony optimization methods

Purpose – The purpose of this paper is to optimize the frictional input parameters related to the yarn and woven fabric samples. Indeed, using metaheuristic techniques for optimization, it helps to attempt the best quality appearance of garment, by analysing their effects and relationships with the bagging behaviour of tested fabrics before and after bagging test. Using metaheuristic techniques allows us to select widely the minimal residual bagging properties and the optimized inputs to adjust them for this goal. Design/methodology/approach – The metaheuristic methods were applied and discussed. Hence, the genetic algorithms (GA) and ant colony optimization (ACO) technique results are compared to select the best residual bagging behaviour and their correspondent parameters. The statistical analysis steps were implemented using Taguchi experimental design thanks to Minitab 14 software. The modelling methodology analysed in this paper deals with the linear regression method application and analysis to prepare to the optimization steps. Findings – The regression results are essential for evaluate the effectiveness of the relationships founded between inputs and outputs parameters and for their optimizations in the design of interest. Practical implications – This study is interesting for denim consumers and industrial applications during long and repetitive uses. Undoubtedly, the denim garments remained the largely used and consumed, hence, this particularity proves the necessity to study it in order to optimize the bagging phenomenon which occurs as function of number of uses. Although it is fashionable to have bagging, the denim fabric remains, in contrast with the worsted ones, the most popular fabric to produce garments. Moreover, regarding this characteristic, the large uses and the acceptable value of denim fabrics, their aesthetic appearance behaviour due to bagging phenomenon can be analysed and optimized accurately because compared to worsted fabrics, they have a high value and the repetitive tests to investigate widely bagged zones can fall the industrial. The paper has practical implications in the clothing appearance and other textile industry, especially in the weaving process when friction forms (yarn-to-yarn, yarn-to-metal frictions) and stresses are drastic. This can help to understand why residual bagging behaviour remained after garment uses due to the internal stress and excessive extensions. Originality/value – Until now, there is no work dealing with the optimization of bagging behaviour using metaheuristic techniques. Indeed, all investigations are focused on the evaluation and theoretical modelling based on the multi linear regression analysis. It is notable that the metaheuristic techniques such as ACO and GA are used to optimize some difficult problems but not yet in the textile field excepting some studies using the GA. Besides, there is no sufficiently information to evaluate, predict and optimize the effect of the yarn-to-yarn friction as well as metal-to-yarn one on the residual bagging behaviour. Several and different denim fabrics within their different characteristics are investigated to widen the experimental analysis and thus to generalize the results in the experimental design of interest.

Recovery velocity evaluation of bagged denim fabrics as function of frictional parameters

Purpose – The purpose of this paper is to predict the bagging recovery velocity of bagged denim fabric samples. Hence, the authors attempt to carry out a model highlighting and explaining the impact of some considered frictional parameters such as yarn-to-yarn friction expressed as weft yarn rigidity parameter and metal-to-fabric friction expressed by mean frictional coefficient parameter. Design/methodology/approach – The statistical analysis steps were implemented using experimental design type Taguchi and thanks to Minitab 14 software. The modeling methodology analyzed in this paper deals with the linear regression method application and analysis. The predictive power of the obtained model is evaluated by comparing the estimated recovery velocity (theoretical) with the actual values. These comparative values are measured after the bagging test and during the relaxation time of the denim fabric samples. The regression coefficient (R2) values as well as the statistical tests (p-values, analysis of variance results) were investigated, discussed and analyzed to improve the findings. Findings – According to the statistical results given by Taguchi analysis findings, the regression model is very significant (p-regression=0.04 and R2=97 percent) which explains widely the possibility of bagging behavior prediction in the studied experimental field of interest. Indeed the variation (the increase or the decrease) of the frictional input parameters values caused, as a result, the variation of the whole appearance and the shape of the bagged zone expressed by the residual bagging height variations. In spite of their similar compositions and characteristics, the woven bagged fabrics presented differently behaviors in terms of the bagging recovery and kinetic velocity values. After relaxation times which are not the same and relative to different fabric samples, it may be concluded that bagging behavior remained function of the internal frictional stresses, especially yarn-to-yarn and metal-to-fabric ones. Practical implications – This study is interesting for denim consumers and industrial applications during long and repetitive uses. The paper has practical implications in the clothing appearance and other textile industry, especially in the weaving process when friction forms (yarn-to-yarn, yarn-to-metal frictions) and stresses are drastic. In fact, in terms of the importance to the industrial producers of the materials it helps to provide a first step in an attempt for a better understanding of the stresses involved in bagging of woven fabrics in general and denim fabrics particularly due to important frictional input contributions. They provide the basis for the development of fabrics that can withstand bagging problems. This research may also put forward improved methods of measuring bagginess as function of frictional parameters in order to optimize (minimize) their effects on the bagging behaviors before and after repetitive uses. These experimental, statistical and theoretical findings may be used to predict bagginess of fabrics based on their properties and prevent industrial from the most significant and influential inputs which should be adjusted accurately. This work allows industrial, also, to make more attention, in case of a high-quality level to ensure, to optimize and review yarn behaviors used to produce fabrics against drastic solicitations and minimize frictions forms during experimental spinning and weaving processes. Originality/value – Until now, there is no sufficient information to evaluate and predict the effect of the yarn-to-yarn friction as well as metal-to-yarn one on the residual bagging behavior. Besides, there is no work that deals with the kinetic recovery evolution as function of frictional inputs to explain accurately the bagging behavior evolution during relaxation time. Therefore, this present work is to investigate and model the residual bagging recovery velocity after bagging test as function of the frictional input parameters of both denim yarn and fabric samples (expressed by the friction caused due to contact from conformator to fabric).

Study on the bagging behavior of knitted fabrics by shape memory polyurethane fiber

The shape memory polyurethane (SMPU) fabrics were knitted with different SMPU fiber contents for the investigation of its bagging behaviour in this paper. The bagging deformation and recovery of these SMPU-knitted fabrics were determined at different temperatures to evaluate its temperature sensitivity. Our experimental results show that the bagging behavior of the SMPU-knitted fabrics is highly correlated with the amount of SMPU fibers knitted inside the SMPU fabrics. The switching temperature of the SMPU-knitted fabrics is found to be above the phase transfer temperature of SMPU. A comparison between Lycra and SMPU-knitted fabrics is also conducted to validate the shape memory bagging behavior of SMPU-knitted fabrics.

Analyzing the Effect of Fiber, Yarn and Fabric Variables on Bagging Behavior of Single Jersey Weft Knitted Fabrics

This research investigates the effect of fiber, yarn and fabric variables on the bagging behavior of single jersey weft knitted fabrics interpreted in terms of bagging fatigue percentage. In order to estimate the optimum process conditions and to examine the individual effects of each controllable factor on a particular response, Taguchi's experimental design was used. The controllable factors considered in this research are blending ratio, yarn twist and count, fabric structure and fabric density. The findings show that fabric structure has the largest effect on the fabric bagging. Factor yarn twist is second and is followed by fabric density, blend ratio and yarn count. The optimum conditions to achieve the least bagging fatigue ratio were determined.

The effect of fabric design and weft density on bagging behavior of cotton woven fabrics

This research investigates the effect of weave design and fabric weft density on the bagging behavior of cotton woven fabric interpreted in terms of fabric mechanical properties using FAST system. The results of this research show that the shear rigidity and formability significantly increased with weft density, whereas most fabric bagging parameters including bagging fatigue, resistance, hysteresis, and residual bagging hysteresis decreased accordingly. However, the weft density has no significant influence on residual bagging height. Moreover, the result of this work revealed that cotton fabric with a twill 2/2 structure exhibited the lowest shear rigidity and the highest formability which, in turn, led to the highest bagging parameters including bagging fatigue, resistance, hysteresis and residual bagging hysteresis, and the lowest residual bagging height among plain, twill 3/1, and hopsack weave designs.

Contributions of in‐plane fabric tensile properties in woven fabric bagging behaviour using a new developed test method

To investigate the relation of in‐plane fabric tensile properties with woven fabrics bagging behavior, a new test method was developed and a real time data acquisition and strain gauge technique were used. The bagging procedure was carried out while the woven fabric tensile deformations along warp and weft directions were measured. The fabric bagging behavior was characterized by bagging resistance, bagging fatigue, residual bagging height and residual bagging hysteresis. The experimental results show that the bagging load, work, hysteresis, residual hysteresis and fatigue are highly linearly correlated with corresponding parameters in warp and weft directions. An empirical relationship obtained between residual bagging height and bagging fatigue and resistance (R2=0.83) suggests that the proposed new test method is able to evaluate bagging behavior of fabrics.

Bagging of Woven Fabrics: The Rheological Mechanism and Predictions

The influence of fibre, yarn, and fabric properties on the bagging behaviour of woven fabrics is studied by developing rheological models and comparing them with the results of statistical analysis on experimental measurements. Three rheological models are developed to describe the bagging-deformation features at different stages of bagging processes, from which three types of deformation energy are identified: elastic and viscoelastic energies of the fibres, and the frictional-deformation energy resulting from the frictional slippage between fibres and yarns. To evaluate the theoretical analysis, 24 fabrics were tested to determine their bagging behaviour, the mechanical properties of constituent fibres and yarns, and fabric structural features. Statistical regression analysis is applied to derive the parameters describing bagging fatigue and their relationships with the fibre and yarn mechanical properties and fabric structural features. A comparison of the experimental results with the theoretical analysis indicates that a decrease in the work of loading with repeated bagging deformation resulted from two basic causes: the stress relaxation of the fibres due to the fibres' viscoelastic behaviour and the friction between fibres and between yarns due to frictional restraints inherent in the fabric structures. The three parameters (Q o, U σ) describing the fabric-fatigue process are shown to be dependent on fibre and yarn mechanical properties and fabric structural parameters, such as fabric thickness, weight, cover factor, and interlacing points. Using the regression equations for the three parameters (Q o, U σ), we show that the bagging-fatigue behaviour and fabric-residual-bagging height are predictable from the fundamental fibre and yarn mechanical properties and fabric structural parameters, indicating that a subjective perception of fabric-bagging is also predictable from the parameters.