Boubaker Jaouachi

Evaluation of wet pneumatically spliced elastic denim yarns with fuzzy theory

This paper focuses on the evaluation of wet pneumatic spliced elastic yarn performance using the fuzzy logic theory. Referring to Altinozs study (Altinoz & Winchester, 2001), fuzzy logic method allows a new level of flexibility over traditional mathematical methods in defining and evaluating constraints. The application of fuzzy rules and fuzzy memberships is discussed and investigated. Using the suitable parameters and optimized splicing conditions such as yarn count, length of splice and duration of water joining, the results show that triangular membership gives better fitting of experimental results. Compared to the experimental properties, theoretical performances of the wet splice can be predicted in the desired field of interest. Our results also indicate that the splice performance remains influenced especially by the elastic yarn count and the splice length as well. In this work, the experts opinions using our fuzzy logic model were formalized with precision. Compared with regression model, the fuzzy model gives a more accurate prediction than the regression model.

Mechanical properties and appearance of wet-spliced cotton/elastane yarns

Abstract Experimental design method and principal component analyses were used to determine the most relevant parameters for the mechanical properties and the appearance of wet-spliced cotton/ elastane yarns. The results proved that a high-quality splice could be obtained in optimal conditions. Yarn linear density influenced both the mechanical properties and the splice appearance. The splice strength was improved when joining air duration was increased. In contrast with the classical yarns, the increase in the length of the yarn tails had no effect on the splice strength. Moreover, increasing the joining water duration and the yarn tail length, respectively improved the splice appearance.

Evaluation of residual bagging volume using 3D image analysis technique

This work deals with the evaluation of the residual bagged fabric volumes using image analysis technique. Indeed, image processing method was applied and compared for denim bagged woven samples. Hence, seven different denim fabrics are evaluated and investigated in order to measure their residual bagging volumes. Different inputs characterizing denim garment specimens are also tested to analyze and evaluate their effects on the bagging volume values. To extract and evaluate residual bagging volume, overall captured images of bagged fabrics based on 3D analysis of intensity images were processed and analyzed. Regarding the findings obtained, the image analysis technique offers good results and helps, in 3D distribution, to evaluate objectively the residual bagging volume of denim samples. Besides, referring to the results, the residual volume which affects negatively bagging appearance can be improved when some influential inputs are widely studied and controlled. Furthermore, based on the influential input parameters contributions, it may be concluded that an increase of weft yarns density (pick/cm) increases the residual bagging volume of denim fabrics. However, when the energy of compression increased, the residual bagging volume decreased. All results given by image analysis method are improved using the regression method and principal component analysis technique.

Study of knitting factors contribution on residual bagged fabric behaviour

The aim of this work is to analyse and evaluate the contribution of some knitting machine and yarn structure parameters on the residual bagging height using an experimental Taguchi design method. Besides, the effects of each input parameter as well as their interactions are discussed. In our experimental field of interest, the results show that the most important factors are the tightness factor and the gauge; thanks to their most influential contributions represent on the residual height behaviour of bagged fabrics. Based on a comparative analysis, our findings show that yarn composition affects widely the residual bagging height because it presents a non-negligible contribution on the height of bagged samples. However, amongst the overall investigated interactions between input parameters, only some influential ones give more explanation about how to decrease the residual bagging height of knitted fabrics.

Evaluating sewing thread consumption of jean pants using fuzzy and regression methods

This study focuses on the evaluation of sewing thread consumption of jean pants using the fuzzy logic theory. Referring to literature works, fuzzy logic method remains an accurate method that allows a new level of flexibility over traditional mathematical methods in defining and evaluating constraints. The application of fuzzy rules and fuzzy memberships is discussed and investigated. Using the influential parameters and optimized sewing conditions (suitable adjusted regulations of each input) such as thread composition, needle size and fabric weight, the results show that sigmoid membership gives better fitting of experimental results. Compared with the experimental consumptions, theoretical findings of the jean pant can be predicted in the desired field of interest. The results also indicate that the pant consumed thread remains influenced especially by the thread properties and the needle size as well. Compared with regression model, the fuzzy model gives a more accurate prediction and provides widely the amount of sewing thread than the regression model.

Influence of some sewing parameters upon the sewing efficiency of denim fabrics

Abstract This paper reports an experimental investigation of the effect of the seam threads linear density, the stitch density and some fabric properties on the seam efficiency. Furthermore, on the basis of the seam quality parameters, regression models were determined in order to predict seam efficiency. In this work, 18 denim fabrics, having different compositions and masses, were sewn with two commercial sewing threads. Their performances, ranked according to the seam quality, were also determined. The seam efficiency was calculated by determining of the seam tensile strength and the fabric tensile strength. It was concluded that the increase in the seam thread linear density increases the seam efficiency, as well as the stitch density. However, the fabric mass has a random effect on seam efficiency. About the composition, we conclude that the seam efficiency decreases with polyester but increases with elastane. According to the seam direction, it was found that, in the weft direction, the seam efficiency was more important than in the warp direction.

Mechanical behavior of flax/polypropylene commingled nonwoven at dry scale: Influence of process parameters:

Currently, nonwoven fabrics made with natural and thermoplastic commingled fibers have been extensively used in the composite industry due to their light weight and low processing and material costs. As two key parameters in the manufacturing of nonwoven fabrics, the needle-punching and material surface densities influence strongly the mechanical properties of nonwoven fabrics and their reinforced composite parts. Compared to most studies focused on the composite stage, the present experimental investigation is performed at the dry fabric stage, and the influence of the needle-punching and material surface densities on the mechanical behavior of nonwoven fabrics will be analyzed through tensile and bending tests. The results show that increasing the material surface of the nonwoven fabric leads to a better mechanical behavior, but that such variations do not modify the phenomenon of anisotropy of nonwoven fabrics. By contrast, increasing the needle-punching density can strengthen generally the homogeneity of nonwoven fabrics.

Waste factor evaluation using theoretical and experimental jean pants consumptions

This paper focuses on a contribution of modeling consumption of sewing thread during clothing jeans classic pants. In fact, to determine accurately the amount of sewed thread used by assembly type needs to model widely the amount of thread in each stitch type taking into consideration the waste factor contributions. Several factors determine the extent of thread consumption in any sewn garment, such as seam length, stitch density, seam types, and material thickness. Nevertheless, the variability of factors depends on the different styles of garment that let thread consumption of sewn product categories such as jean pants, shirts, and jacket to be variable. However, these factors are not constant with the different styles of garment. Hence, thread consumption is never a standard for sewn product categories such as trousers, jackets, shirts, products lingerie, and footwear. Regarding the linear regression method results, it may be concluded that waste factor is correlated accurately with the experimental sewing thread consumption. Our findings show that developed theoretical consumption equations give more accurate values compared to experimental ones. Likewise, taking account of waste factor in our theoretical analysis helps to obtain objectively the real sewing thread consumption value.

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 varian...

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...