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Environmental impact and changes are becoming essential in textile and yarn industries, where reliable measurement of parameters related to processing harmful substances needs to be examined. Such findings can be cumulated using smart assessment like life cycle analysis. The ecological impact category, supply chain, and climate-changing factors were considered for the necessary assessment.

This paper applies the Life Cycle Assessment technique in the textile and yarn industry to estimate critical environmental potentials. The critical input for the fabric and yarn industry was put in the GaBi software model to estimate various environmental potentials.

Global warming potential, electricity, and raw cotton consumption in the fabric and yarn industry were critical concerns where attention should be focused on minimizing environmental potentials from cradle to gate assessment.

This qualitative study is made via the industry case-wise inputs and outputs, which can vary with demographic conditions. Some machine and human constraints have not been implemented in modelling life cycle model for smart simulation. Smart simulation helps in linking different parameters and simulates their combined effects on the product life cycle.

This modelling approach will help access pollution constituents in different supply chain production processes and optimize them simultaneously.

The raw data used in this analysis are collected from an Indian small scale textile industry. In the textile fabrication industry, earlier assessments were carried out in cotton generation, impact of PET, cradle to grave assessment of textile products and garment processing only. In this research the smart model is drawn to consider each input parameter of yarn and textile fabric to determine the criticality of each input in this assessment. This article mainly talks about life cycle and circular supply assessment applied to first time for both cotton to yarn processing and yarn to fabric industry for necessary estimation of environment potentials.

The purpose of this paper is to examine the effects of coating process parameters (base fabric, coating material, coating technique and production parameters) on mechanical properties of coated fabrics.

In this research, 24 coated fabrics were produced under controlled production conditions by using two cotton base fabrics and two coating materials as polyurethane (PU), PU/silicone in order to study how coating affects some of the base fabric's mechanical properties such as breaking strength, breaking elongation, tear strength, bursting strength, bending rigidity and abrasion resistance. The measured data were evaluated with variance analysis to determine the effects of the coating parameters at 95 per cent confidence level.

Breaking strength shows increments for almost all fabrics, whereas breaking elongation values decreased by coating application. Coating has a very clear influence on tear strength of coated fabrics due to the penetration of coating material into the fabric structure. Changes in bursting strength are not similar for two base fabrics with systematically changed production parameters. Coating improves all measured parameters of bending rigidity. Coating application enhances abrasion resistance though some broken fibers are observed on the fabric surface in scanning electron microscopy investigation.

In the past few years, the researches on this area focused on investigating the effects of coating materials and layers on tensile properties. This study comprehensively examines the effects of several coating parameters on mechanical properties such as breaking strength, breaking elongation, tear strength, bursting strength, bending rigidity and abrasion resistance.

The purpose of this paper is to propose a rational and complete design scheme of seam type of outdoor clothing, so as to improve the seam efficiency and appearance of outdoor clothing, as well as to provide an optimal seam base for the subsequent pressure adhesive process.

Four types of common outdoor fabrics and four seam types were selected. Seam strength and thickness were measured. Seam efficiency and seam thickness strain were calculated to evaluate seam quality. Multiple linear regression analysis was adopted to analyze the influence of seam type essential factors on seam strength.

Among the component factors of seam type, based on two stitches, seam strength was significantly affected by stitch distance, followed by fabric layer on the seam side. The increase of stitch and the interaction among fabrics can effectively improve the seam efficiency. The methods are as follows: the increase of stitches, stitch distance shortening, the increase of fabric layers, etc. The change of seam type had no significant influence on seam thickness strain. A seam-type design scheme of outdoor clothing with good mechanical and appearance properties was designed by choosing the seam types FX₁, FX₂ and FX₄.

This paper designed a practical scheme of seam-type design of outdoor clothing, which has been applied in the industrial production process. It is important for guiding the improvement of seam quality and the production efficiency of outdoor clothing.

The purpose of this paper is to present a dynamic analysis on the thermal and electrical properties of fabrics under wet conditions.

A purpose‐built apparatus is applied to test the thermal and electrical properties of textiles in moisture absorption and liberation process. Relation between temperature and resistance of a cotton/polyester double‐layer fabric is also analysed.

The surface temperature of textiles shows three different stages in the process. The electrical resistance is linearly related to the reciprocal of the moisture regain of fabrics. In the moisture absorption and liberation process, surface temperature of cotton layer is higher than that of polyester layer. And the electrical resistance of cotton layer decreases more quickly than that of polyester layer. The electrical resistance changes earlier than surface temperature in the moisture‐liberation process.

The paper is helpful in not only the designing of sportswear, but also the devising of moisture‐testing apparatus.

A dynamic testing method is applied to characterize the thermal and electrical properties of textiles.

The target of the current work is the creation of a model for the prediction of the air permeability of the woven fabrics and the water content of the fabrics after the vacuum drying.

There have been produced 30 different woven fabrics under certain weft and warp densities. The values of the air permeability and water content after the vacuum drying have been measured using standard laboratory techniques. The structural parameters of the fabrics and the measured values have been correlated using techniques like multiple linear regression and Artificial Neural Networks (ANN). The ANN and especially the generalized regression ANN permit the prediction of the air permeability of the fabrics and consequently of the water content after vacuum drying. The performance of the related models has been evaluated by comparing the predicted values with the respective experimental ones.

The predicted values from the nonlinear models approach satisfactorily the experimental results. Although air permeability of the textile fabrics is a complex phenomenon, the nonlinear modeling becomes a useful tool for its prediction based on the structural data of the woven fabrics.

The air permeability and water content modeling support the prediction of the related physical properties of the fabric based on the design parameters only. The vacuum drying performance estimation supports the optimization of the industrial drying procedure.

Some areas of the apparel industry, such as folding and sewing, are still labor intensive. The purpose of this paper is to present a new fuzzy visual servoing strategy for the folding of fabric strips by robotic manipulators.

Three stages of the folding task are distinguished experimentally, the initial laying, the true folding, and the final laying. An indirect visual servoing fuzzy system, employing two cameras, is developed to guide the robot along each of the stages.

The proposed scheme manages to successfully fold some of the tested materials. The experimental results are promising and well within the limitations posed by both the employed equipment and the nature of the handled materials.

This study is limited to rectangular strips of fabrics and does not consider the speed of the process.

The resulting system provides a stepping stone for the introduction of automation to currently labor‐intensive areas of the apparel industry.

The separate folding stages reduce the complexity of the overall system and the introduced visually extracted features allow a closer monitoring of the process.

Enzyme treatment technologies are frequently applied in textile processing for the modification of fabric handle appearance and other surface characteristics in regard to cotton and cotton blended fabrics. The purpose of this paper is to understand the impact of enzyme treatments on fabric preparation, dyeing, and finishing processes of woven fabrics. In particular, certain mechanical and surface properties of 100 percent cotton interlock knitted fabrics after treatment with a cellulase enzyme.

Interlock knitted fabrics were used for this research. These cotton fabrics were treated with experimental Trichoderma reesei cellulases containing different cellulase profiles and treatment was carried out under laboratory conditions. The effects of cellulase treatment on weft knitted fabric regarding mechanical and surface properties were evaluated using the KES‐FB Kawabata evaluation system. The influence of enzyme treatments, friction, and geometrical roughness on the face and reverse side of interlock knitted fabrics were discussed in comparison with untreated interlock knitted fabric.

After each of the enzyme treatments, the interlock knitted fabrics lost part of their weight and, therefore, they became thinner. Furthermore, the extension properties become higher in both directions with regard to the untreated knitted fabric for all used enzymes and carried out treatments.

The paper usefully analyzes changes in the extension and surface properties of enzyme‐treated interlock knitted fabrics by investigating the influence of whole or enriched endoglucanases celullases of Trihoderma reesei under different treatment conditions.

The weft-knitted two-side jacquard fabric has the characteristics of complicated design principle and hard technical design. The purpose of this paper is to realize the computer-aided design of weft-knitted two-side jacquard fabric, and provide a certain reference for the development of this type of fabric.

The weft-knitted two-side jacquard fabric is divided into weft-knitted two-side similar pattern jacquard fabric and weft-knitted two-side independent pattern jacquard fabric. In order to achieve the purpose of this study, firstly, the structural characteristic of weft-knitted two-side jacquard fabric is analyzed. Then, the design principle of weft-knitted two-side jacquard fabric is studied. Next, the technical model of weft-knitted two-side jacquard fabric is established. Finally, the CAD flow chart of weft-knitted two-side jacquard fabric is proposed to realize the rapid product development.

Based on the above method, through the development example of weft two-side similar pattern jacquard fabric and weft two-side independent pattern jacquard fabric, the computer-aided design of the weft two-side jacquard fabric is verified.

Because of limited research studies, three-dimensional computer-aided design of weft-knitted two-side jacquard fabric loop structure will be studied in the further research, and the technical design speed needs to be improved to meet the needs of large patterns and positioning patterns.

The computer-aided design of weft-knitted two-side jacquard fabric will offer a certain reference for product development, technical principles, performance research and computer simulation for the in-depth study of the fabric.

The computer-aided design of weft-knitted two-side jacquard fabric will simplify the fabric design process and improve the efficiency of new fabric development, and provide the industries a time-saving and cost-saving approach for new fabrics development.

The author analyzes the structural characteristic of the fabric by the physical fabric, summarizes design principle of the fabric through production process, uses mathematical methods to establish a three-dimensional technical model of the fabric, and proposes the CAD flow chart of weft-knitted two-side jacquard fabric, which has good theoretical significance and practice of weft-knitted two-side jacquard fabric.

Thermoplastic polymer fabrics are normally heat set to make them dimensionally stable. These fabrics in garment panel form may again be exposed to heat during the processes such as bonding, sublimation printing and cause to change their dimensions. The purpose of this paper is to investigate the response of polyester yarns in knitted fabrics to heat setting and post-heat treatments.

In this study, the thermal shrinkage behaviour of heat set polyester knitted fabrics when subjected to post-heat treatment processes are analyzed using differential scanning calorimetry (DSC) and analysis of fabric shrinkage. DSC is a thermo-analytical technique that measures the difference in the amount of heat needed to increase the temperature of the sample and the reference. A heat flux versus temperature curve is one of the results of a DSC experiment. The polymer structure and morphology of polyester heat-treated and post-heat–treated fabrics were determined by examining the DSC thermograms.

Heat setting and post-heat setting causes the effective temperature of polyester to change. Effective temperature occurred around 160°C for fabrics heat set at low temperatures and increases as the heat setting temperature increases. Post-heat treatments cause to elevate the effective temperature. Shrinkage of fabrics below the effective temperature is not statistically significant while the shrinkage at higher temperatures is significant. Effective temperature is the main determinant of thermal shrinkage behaviour of polyester.

The study reveals the significance of the effective temperature of polyester on heat treatments and post-heat treatments. The study revealed that heat-setting temperature is a primary determinant of the thermal stability of polyester fabric that are subjected to heat treatments.

In the fabric manufacturing industry, various unfavorable factors, including machine fault and yarn breakage, can easily cause fabric defects and affect product quality, begetting huge economic losses to enterprises. Thus, automatic fabric defect detection systems have become an important development direction. Herein, the most common defects in the fabric production process, like ribbon yarn, broken yarn, cotton ball, holes, yarn shedding and stains, are detected. Current fabric defect detection systems afford low detection accuracy and a high missed detection rate for small target fabric defects. Therefore, this study proposes deep learning technology for automatically detecting fabric defects by improving the YOLOv5s target detection algorithm. The improved algorithm is termed YOLOv5s-4SCK, which can effectively detect fabric defects. This study aims to discuss the aforementioned issues.

Specifically, based on the YOLOv5s algorithm, first, the structure of YOLOv5s is modified to add a small target detection layer, fully utilize deep and shallow features and reduce the missed detection rate of small target fabric defects. Second, the integration of CARAFE upsampling enables the effective retention of feature information and maintenance of a certain computational efficiency, thereby improving the detection accuracy. Finally, the K-Means++ clustering algorithm is used to analyze the position of the center point of the prior box to better obtain the anchor box and improve the average accuracy and evaluation index of detection.

The research results show that the YOLOv5s-4SCK algorithm increases the accuracy by 4.1% and the detection speed by 2 f.s-1 compared to the original YOLOv5s algorithm, and it effectively improves the original YOLOv5s problem of high missed detection rate of small targets.

The YOLOv5s-4SCK proposed in this paper can effectively reduce the missed detection rate of fabric defects, improve the detection efficiency and has certain industrial value.

The proposed algorithm can quickly identify fabric defects, effectively improving the detection rate. In the future, the proposed algorithm will be applied in the actual industry.

Automatic fabric defect detection reduces the manpower of inspectors, and the proposed YOLOv5s-4SCK algorithm is also suitable for other recognition fields.

The proposed YOLOv5s-4SCK algorithm has been tested using real cloth to ensure its accuracy, and its performance is better than the original YOLOv5s algorithm.