Volume 24, Issue 1

Warp knitting creates very challenging dynamics due to its high production speeds. On the one hand, this makes it method of choice for many products in various fields. On the other hand, not all materials are suitable for such high productivity. With the current generation of machines being limited to only achieve their maximum speed of around 4,400 min −1 with highly elastic yarns, it is desired to gain a deeper insight into yarn behavior in such highly dynamic environments. Among other influences, resonance effects gain high significance as they may result in high loads on the used materials; therefore, yarn breakages interrupt the production and decrease the quality of the product. To extend the material choice, especially high-performance fibers, for high productivity, a deep understanding of the intrinsic properties of the yarn is required. In particular, the viscoelastic properties are of importance. This study proposes a method to determine these characteristics using the dynamic mechanical analysis method. For the purpose of finding the damping in the transversal direction to the yarn axis, the variant of free oscillation is chosen. For the trials, a high-speed camera is suspended above a testing rig. On this rig, a yarn sample is clamped and then displaced from its rest position. The resulting oscillation is recorded and later extracted from the video. From the decrement of the maxima of the amplitude and corresponding time intervals, the damping factor is determined. It decreases with higher initial deflection. Summarised the developed trial setup proved suitable for the determination of the viscoelastic properties in transversal direction.

The omni-channel strategy, which presents a continuous purchasing experience to consumers and which provides the full integration of different channels, promises the consumers an effortless, simple, and issueless buying process. In this context, this study aimed to analyze the consumer-preferred omni-channel implementations in clothing sector. At the same time, it also aimed to make suggestions, which are based on consumer desires, to clothing producers and marketers in the light of the obtained findings. An online survey is conducted to volunteer Turkish citizens, who are at the age of 18 or elder and who are the residents of Türkiye, in order to be able to obtain the data, which are used within the scope of this study. The relationships between omni-channel implementations are analyzed using statistical methods, such as exploratory factor analysis, t -test, and analysis of variance, on the basis of clothing sector. According to the obtained study results, Turkish consumers give great importance to omni-channel strategy and its elements. More specifically, they give great importance to the integration between physical and online channels, and they prefer a full information, customer services, and price integration between channels. The study results indicate that the consumers are aware of the advantages of omni-channel strategy and they demand these factors from enterprises, brands, and retailers. The study is detailed and comprehensive on the basis of both scope and used methods. All studies are designed on the basis of clothing sector, and all analyses and evaluations are actualized on this basis. In this context, this study differs and individuates from the other studies in the literature due to these aspects. This study both contributes to the deficiencies in sector’s marketing and retailing areas and to the fulfillment of gap within the literature.

Rotary braiding is widely used in the preparation of high-performance fiber composites. However, neither conventional rotary two-dimensional braiding nor rotary three-dimensional braiding can prepare three-dimensional preforms with low porosity and dense surface yarns. This article designs a three-dimensional cross-linked braiding equipment, describes the mechanism of carrier motion of three-dimensional cross-linked braiding, and obtains a numerical model of three-dimensional cross-linked braided preforms by establishing the spatial coordinate system of the braided chassis and using cubic B-spline curve fitting. The reasons for the large difference between the numerical model of preform and the real fabric are analyzed, and an optimization algorithm is proposed to make the fabric compact by gathering the yarn to the center of the fabric. The experimental samples are braided on a three-dimensional cross-linked braiding machine, and the reliability of the optimization algorithm is verified by comparing the yarn coordinates of the experimental samples with those of the optimized numerical model. The accurate establishment of the geometric model of the preform provides a solid foundation for carrying out the prediction of the mechanical properties of composite materials.

The weft knitted shirt fabric has good elasticity and comfortability, but it is difficult to achieve the formability of woven shirts. In this study, 30D XLANCE ® elastic fibers and 30D Lycra ® elastic fibers were used, which paired with 40S cotton and 75D/36F moisture-absorbing and quick-drying polyester DTY to develop the woven shirt fabrics on a 32 needle/25.4 mm single-sided circular machine. The results indicate that the 30D XLANCE ® knitted shirt fabric has undergone sufficient heat setting treatment, and its mechanical properties are close to those of the standard woven fabric, superior to 30D Lycra ® and 30D XLANCE ® without sufficient heat setting treatment fabrics. The ultraviolet resistance behavior of XLANCE ® fabrics is significantly better than that of Lycra ® fabrics. Meanwhile, the XLANCE ® fabrics after heat setting still maintain the excellent elasticity and resilience, breathability, moisture absorption, and quick drying performance, and the dimensional stability after washing is also very good. In addition, compared with spandex, XLANCE ® fabrics have the lower heat setting temperature, which is beneficial for reducing energy consumption and carbon emissions. It can be considered that XLANCE ® elastic fibers are the ideal raw materials for the knitted woven products.

This study was prompted by the unsustainable issues facing the garment industry and the trend toward digitalisation in the post-coronavirus disease 2019 (COVID-19) pandemic era. COVID-19 substantially affected global trade, which caused significant garment industry stagnation due to embargoes and international restrictions. Consequently, the stagnation led to a significant inventory backlog and hindered product distribution, which compelled garment companies to turn to online commerce. A circular economy (CE) attempts to halt commodity flow and convert waste into resources; therefore, it can alleviate the substantial garment industry pollution and waste produced under a linear economy and maximise product life cycles. Industrial Revolution 4.0 incorporates technological innovation and information technology to transform the garment industry, which technologically enhances manufacturing intelligence and inspires garment industry transformation into a CE. This systematic literature review discusses the necessity of transforming the garment industry into a CE and the technological advantages and challenges to promoting sustainable garment industry development. The findings demonstrated that transforming the garment industry into a CE can not only resolve its environmental pollution and excess supply issues but can also accommodate new supply and demand requirements, such as market digitisation, consumer personalisation, and industry chain transparency. Finally, a technology integration initiative was proposed to promote garment industry transformation into a CE by digitising product development to achieve sustainable development.

Users’ Kansei image preferences have become one of the most important factors influencing purchase decisions. However, defining Kansei image can be complex. To address this issue, researchers have widely applied back-propagation neural networks due to their capacity to handle extensive data, adaptively adjust weights and biases, conduct multi-class classification and regression predictions, and offer interpretability analysis, among other features. In this study, a clothing-style design model based on users’ Kansei image cognition is proposed, using collarless T-shirts as an example. Furthermore, the attributes of T-shirt patterns are quantified using parametric graphics principles, and a semantic scale system for emotions is established through user research. The quantified sample data and corresponding semantic scale scores are then used as inputs for training a back-propagation neural network algorithm. Consequently, a design model grounded in users’ Kansei image cognition is developed, resulting in five optimal clothing design forms across various Kansei image categories. Additionally, the styles are showcased through the Style 3D platform, and the design evaluation is presented using radar charts. The results demonstrate that the five female T-shirt designs generated by the model align with users’ style preferences based on Kansei image.

Although the color characteristics of She nationality clothing are slightly different, there are multiple similarities in shapes and textures. Therefore, it is difficult to effectively distinguish different branches of She nationality clothing. To address this problem, this article, taking into account color feature fusion, proposes a recognition method based on a hybrid algorithm of particle swarm optimization and support vector machine (PSO-SVM). First, the color histogram and color moment (CM) feature descriptors were extracted from the five branches of She nationality clothing, and the color feature distribution of each branch was obtained. Then, color feature fusion is performed through optimization and dimensionality reduction of principal components. Furthermore, PSO was introduced to independently optimize parameter combinations. Finally, the different branches of She nationality clothing were automatically recognized. The results demonstrated that the proposed method could effectively distinguish different branches of She nationality clothing. Compared with the recognition accuracy of approaches using single-color histogram and CM feature, the performance of our proposed method was increased by 5.25 and 6.44%, respectively. When the penalty parameter γ \gamma and kernel parameter δ 2 {\delta }^{2} of SVM were 123.29 and 1.16, respectively, the recognition accuracy of the model was the highest, reaching 98.67%. The proposed method could be a reference for the subdivision recognition of She nationality clothing.

This article aimed at providing a new biomechanical three-dimensional dynamic finite element model of the hand–glove combination for exploring the distribution of the overall continuous dynamic contact pressure of the hand with the flexible glove in the state of grabbing an object, and further predicting the accuracy of sensors of wearable smart gloves. The model was validated by garment pressure experiments at eight muscle points. The results showed that the pressure value measured with three flexible gloves was highly consistent with the finite element simulation value. Based on the model, the distribution of dynamic pressure between the soft tissue of the hand and the fabric in the process of flexing the fingers and grabbing external objects were predicted accurately and effectively, which indicated that the model with high accuracy could be applied to evaluate the accuracy of the pressure value collected by sensors of smart gloves. In addition, the model had been confirmed that it has a certain application value. The findings could help to provide a reference for dynamic continuous monitoring equipment or other intelligent wearable devices, and promote the development of the intelligent clothing industry in the future.

Stainless steel fiber exhibits excellent flame retardancy and melting resistance, but it lacks thermal and moisture comfort. To compensate for these shortcomings, stainless steel fiber was blended with Lyocell fiber in ratios of 0/100, 10/90, 20/80, and 30/70%. The blended yarn was then formed into a single-sided plain stitch fabric of stainless steel fiber and finished with a phosphorus–nitrogen flame retardant. Next, the effects of the blending ratio on the fundamental properties, thermal and moisture comfort, and flame retardancy of the blended yarn and its fabric were studied. Considering these parameters alongside cost, the 10% stainless steel fiber-blended fabric was the optimal choice and showed potential applications for updating and upgrading welding service fabrics.

Apparel has the potential to influence the external expression of wearer’s emotional state and can even empower them, making patients’ hospital wearing a crucial factor in their emotional experience and medical treatment. This study aims to investigate the emotional factors that drive patients’ behavioral responses to hospital gowns using the pleasure–arousal–dominance (PAD) model. With the survey conduction and data analysis, the results identified that the color and silhouette of hospital gowns lead to the emotional experience of arousal, while the structure leads to the emotional experience of dominance, which in turn brings patients a high sense of pleasure and further affect their acceptance and willingness to continue wearing hospital gowns. Based on the results of the research, new hospital gowns were designed and validated, which further confirmed the relationship between the attributes of hospital gowns and emotions of patients. Thus, by extending the PAD model to the context of patients’ use of hospital gowns, this study provides designers with a basis for creating emotionally driven atmosphere factors in the development of hospital gowns for the Chinese market that improve acceptance and continuation of hospital gowns, making a valuable contribution to knowledge in this field.

The flame-retardant cotton fabric used for welding protective clothing in the market exhibits insufficient melt hole resistance. We evaluated the stainless steel filament fabric for flame retardancy and melt hole resistance and found that it lacked sufficient comfort. A stainless steel filament and a cotton yarn were plied and twisted together and then woven following a set of specifications. The fabric was finished with a flame retardant, and its performance and flame retardancy were determined. The results indicate that the twist direction during ply twisting affects the fabric performance. Relative to the pure cotton fabric, the stainless steel filament/cotton composite fabric exhibits reduced comfort properties, such as moisture permeability and air permeability, but the mechanical properties and flame retardancy are improved. Ply twisting a stainless steel filament and a pure cotton yarn with an S twist presents certain advantages in enhancing the comprehensive performance of the fabric and exhibits potential for advancements in welding protective clothing.

Commercial disposable facemasks have lower breathability and may cause discomfort after hours of wearing them. Graphene oxide (GO) nanoparticles offer a significant opportunity to improve the breathability of facemask materials. Hence, the current study aimed to investigate the feasibility of incorporating GO in facemask materials. The GO was synthesized from recovered carbon of waste carbon tyre. In this study, two concentrations of GO (0.01 and 0.02%) were used to enhance the comfort properties of the polypropylene (PP) facemask fabric. The GO-coated PP facemask fabrics were characterized for scanning electron microscopy, energy dispersive X-ray, and Raman spectroscopy. The comfort properties were determined using air permeability, water vapour permeability, and moisture management test. Raman analysis revealed distinctive peaks corresponding to GO at approximately 1,300 and 1,500 cm −1 . The GO displayed bumping pieces of particles and a textured surface, with a diameter ranging from 30 to 80 nm. The result of mercury porosimetry shows that the PP fabric coated with 0.02% of GO provided a higher pore diameter and porosity at approximately 21.31 µm and 82.79%, respectively. Due to its high pore diameter and porosity, the PP filter facemask fabric coated with 0.02% GO demonstrated enhanced air permeability, water vapour permeability, and moisture management. These results suggested that the sample possesses favourable breathability properties as compared to the sample without GO. By undertaking this study, GO synthesized from the waste carbon tyre was developed, which can enhance the breathability of fabric materials.

The policy of sustainable development, the need to save natural environmental resources, and the use of waste as raw materials in new production processes allow the use of enzymes in many industries. Enzymatic tanning and chrome tanning are two different methods used in the leather industry to transform raw hides into a durable and usable material. Enzymatic tanning uses natural enzymes that are biodegradable and environmentally friendly. Additionally, enzymatic tanning requires less water and generates less waste than chrome tanning. Moreover, enzymatic tanning can result in softer and more flexible leather with better uniformity. Enzymes selectively break down collagen fibers, resulting in a more even tanning and a consistent leather product. The use of combined enzymatic technologies with non-obvious leather finishing methodologies in tanning is forced by European Union regulations limiting the use of hazardous substances and generating significant amounts of corrosive wastewater for the environment. However, tanning with enzymes is not a perfect process; therefore, this work presents the advantages and disadvantages of tanning with enzymes and describes new technological trends in the tanning industry.

When light falls on the fiber surface, it is absorbed, reflected, or refracted. These three phases of incident light determine, to a great extent, the behavior of lustre of major textile fibers. This article sheds light upon the behavior of some textile fibers, namely, polyethylene terephthalate, cotton, viscose, bamboo, tencel, and modal fibers, in terms of their reflectance percentages in the ultraviolet regions. Also, the direct and indirect band-gap energies of the used textile fibers were also investigated. The findings of this study revealed the significant differences among these used textile fibers in relation to their optical properties. Also, the chemical composition of the used textile fibers was easily identified using near-infrared spectroscopy. Finally, the findings of this study revealed that the used textile fibers are considered good insulators.

In the digital age, virtual simulation images have become an important communication form of Chinese traditional Yue Opera costumes and their culture. Focusing on the lay viewers’ aesthetic experience, we collected 16 subjective evaluations, including favorites of basic design elements, semantic impressions, and high-level aesthetic experience, of 257 participants on 5 virtual simulation pictures of Yue Opera costumes for different characters and used network analysis to explore the possible relationship of the variables. The inferred networks showed that the archetypal aesthetic was more relevant to the costume design elements, emotions, interests, and the sense of high level. The conspicuous clothing, understanding of creative intent, and the desire for cultural knowledge were key “bridges” in the aesthetic process. Although the aesthetic network of each costume varied partially based on character differences, it showed more similarities overall. On the basis of the findings, we discuss the possible theoretical basis of the networks and make practical suggestions for the virtual dissemination of Yue Opera costumes.

The objectives of this study were to apply alternative machine learning (ML) algorithms to predict consumers’ garment fit satisfactions (real fit satisfaction [RFS]) and compare the efficiencies of these algorithms to predict RFS. Skirts made from different fabrics were used as test garments. Mechanical properties of the skirts’ fabrics were assigned as predictor variables to estimate RFS. Study participants’ virtual body models were created by using 3D body scanner and used for virtual fitting. Each participant physically tried on the skirts and evaluated the fit. Participants also viewed the skirt simulations on their avatars and evaluated the virtual fit, which represented participants’ virtual fit satisfactions (VFS). Random Forest (RF), support vector machine (SVM), and conditional tree (CT) algorithms were used to learn from the data to predict participants’ RFSs. The mean correlations between the predicted and observed RFS values in the validation sets were 0.74 (RF), 0.70 (SVM-linear kernel), 0.72 (SVM-radial kernel), and 0.55 (CT). According to the variable importance analysis, VFS had the highest importance among 35 predictor variables. ML is used mostly for sales forecasting and manufacturing purposes in the fashion industry. However, garment fit, which restrains consumers from shopping online, did not get enough attention in ML studies. Besides, the ML algorithms used in fashion and apparel studies are often genetic algorithms and neural networks; therefore, there is a need to test other algorithm types. In this study, we offered alternative ML algorithms (i.e., RF, SVM, and CT) to predict consumers’ garment fit satisfactions.

With the advancement of near-infrared (NIR) spectroscopy and chemometrics technology, non-destructive qualitative testing has been widely applied in many fields. Both wool and cashmere are keratin protein fibers with many similarities in tissue structure, making it very difficult to distinguish between them. In order to achieve rapid and non-destructive identification of wool and cashmere, an improved linear discriminant analysis (ILDA) algorithm combined with NIR spectroscopy technology is proposed. The proposed method can also be used for the classification of extremely similar fibers and substances, with better classification performance. First, the spectral data of wool and cashmere are collected using an NIR spectrometer so as to reduce the influence of noise in the spectra; data preprocessing methods are used to correct the collected fiber spectra. Then, principal component analysis (PCA), linear discriminant analysis (LDA), and ILDA are used to extract the characteristic variables from the spectral data. Finally, the extracted characteristic variables are input into the machine learning algorithm K-nearest neighbor (K-NN) classifier. In the experimental stage, three dimensionality reduction methods (PCA, LDA, and ILDA) are evaluated using the K-NN classification model. The fiber classification accuracy can reach 97% when using the ILDA method for dimensionality reduction. The results show that the proposed method is effective for the qualitative detection of different types of wool and cashmere fibers.

With dry weather and low humidity in autumn and winter, human skin is usually prone to dryness, even leading to itchy skin and other problems, so it is important to do a good job of skin moisturizing. The fabrics produced by using protein fiber have a certain moisturizing effect on human skin. Five types of yarn including collagen fiber, cheese protein fiber, silkworm pupa protein fiber, cashmere protein fiber, and viscose are chosen as veil materials, while nylon/spandex composite fiber is chosen as inner yarn material. Three fabric structures including the weft plain stitch, 1 + 1 mock rib, and 1 + 3 mock rib are selected for the study. Based on the full factorial experimental design method, 15 samples of seamless knitted fabrics are produced using a circular knitting machine. In order to investigate the effects of different veil materials and fabric structure of seamless knitted fabric on skin moisturizing performance, the skin moisture content test and the trans-epidermal water loss test were carried out before and after the fabric samples were wrapped around the skin of 20 participants. The results show that both the veil materials and the fabric structure have significant effects on the skin moisture content. The use of collagen yarn as the veil material and 1 + 1 mock rib as the fabric structure results in better moisturizing effects on human skin. In terms of the trans-epidermal water loss test, the fabric structure has significant effects on the results, while the veil material has no significant effect on it. However, the value of trans-epidermal water loss of the fabric with protein yarn is smaller than that of the fabric with ordinary viscose. Therefore, using cheese protein yarn as the veil material and 1 + 1 mock rib as the fabric structure results in a smaller trans-epidermal water loss value.

To develop antibacterial durability and low yellowing of sports underwear fabric, silver ion polyurethane filaments (Ag + PUFs) were used as base yarn, and polyamide filaments were used as face yarn. Nine fabric samples with different Ag + PUF contents (7, 8, 9, 17, 18, and 19%) were prepared. The fabrics were dyed in light, medium, and dark pink. Ag + PUF was characterized by scanning electron microscopes for the morphology. Antibacterial properties and mechanical properties of Ag + PUF were measured. The antibacterial durability, yellowing, elastic recovery, air, and moisture permeability were tested, and fuzzy mathematics was used for comprehensive evaluation. The results demonstrated that Ag + PUF has good antibacterial properties and mechanical properties. The inhibition rates of the fabric against Escherichia coli and Staphylococcus aureus were 100%. When Ag + PUF content was 18 and 19%, the antibacterial rates of medium pink fabrics both E. coli and S. aureus were 100% after laundering 30 times. The yellowing of the fabric before dyeing was the lowest when Ag + PUF content was 7%. Compared with before dyeing, the yellowing of the fabric decreased by 19.13 % after dyeing. The comprehensive performance of 3# fabric is the best, and it has antibacterial persistence and low yellowing.

This article presents the results of numerical and experimental research on the ballistic performance of soft packages composed of biaxial and triaxial fabrics in various hybrid configurations. The main objective of these studies was to prove the hypothesis that a hybrid package composed of biaxial fabrics, on the impact side of a projectile, and triaxial fabrics, on the backside, exhibits greater ballistic efficiency than a package entirely composed of biaxial or triaxial fabrics. The research was conducted by shooting packages consisting of 30 layers of fabrics using a Parabellum 9 × 19 full metal jacket projectile, with a striking velocity of 380 m/s, after placing the packages on a Roma No.1 plasticine substrate. The analysis involved the deformation depth of the plasticine substrate and the perforation ratio of the packages. Optimisation studies revealed that the optimal package configuration should consist of 9 layers of biaxial fabrics on the projectile impact side and 21 layers of triaxial fabrics on the backside, indicating a biaxial to triaxial fabric ratio of approximately 1:3.

Given problems such as the late start of gender awareness education in China, the gender blurring in preschooler’s clothing, the lack of integrating gender awareness elements into preschooler’s clothing, etc., using children’s sensory functions such as vision, touch, and hearing, a phonetic intelligence module with alarm sounds and warning words is implanted into special parts of children’s clothing. When children gently touch the part, it can make a sound. This kind of smart clothing for preschoolers, which is both interesting and educational, enables children to understand gender knowledge more intuitively, have a certain gender awareness to better protect their private parts of the body, and develop a correct view of gender roles and a sound personality.

The aim of this article is to determine the differences in the physical dimensions of the female body that form the basis of the clothing size system and compare their deviations within the three regions of the Republic of Croatia. Due to the changes in the dimensions and shape of the human body, there is a need to adjust clothing in order to achieve the best possible fit. A systematic consideration of the fit of clothing includes investigation of a number of elements and factors, especially those based on anthropometric knowledge. The results of anthropometric measurements performed on a representative sample determine the body dimensions of the measured population. By sorting and grouping the data of body measurements, clothing sizes are created, with significant differences in body shape and body proportions of individual population groups. In the clothing size system, individual body dimensions define the clothing size and form a scale determined by a norm that prescribes body shape based on two dimensions of girths, where the measurement of bust girth is the basic measurement, and the body height is the dependent variable. This research was carried out on a sample of 940 women from the region of Slavonia, 1,109 women from the region of Dalmatia, and 799 women from the City of Zagreb, classified into seven age groups. The statistical processing of the results, i.e., the method of principal components, the values of the observed body measurements, and the representation of certain categories of bust girth and body size in the measured population of each region were determined.

As a kind of dress combining traditional and modern design, pleated cheongsam is becoming increasingly popular among Chinese users. However, the current design of pleated cheongsam has the problem of mismatch with users’ modern aesthetics and demands, which causes serious homogenization of pleated cheongsam and low sales volume. Therefore, the optimal design of pleated cheongsam was discussed from three aspects:consumer demands, design features, and comprehensive evaluation. The Kano model was used to sort out 12 user demands in three aspects: functionality, usability, and emotion. The House Of Quality (HOQ) method was used to establish the mapping matrix of “user demand-design requirement,” and the priority of 11 design requirements was determined. Finally, the best optimization proposal was screened and evaluated by the Pugh matrix and the live streaming data of pleated cheongsam brand. The experimental results demonstrate that the Kano–HOQ–Pugh model provides a scientific and engineered attribute framework for improving the acceptability and attractiveness of pleated cheongsam and provides a theoretical basis for brands to develop pleated cheongsams with ethnicity, modernity, and differentiation.

The factors of increasing productivity, reducing the cost, and the quality improvement are the most important research concerns in weaving machinery. Increasing the effectiveness and productivity of production was achieved by increasing the operating time and efficiency of weaving looms. Thus, manufacturers of weaving equipment attempt to minimize factors that limit the production speed and production conditions. The heald frame is one of the most important parts of the weaving machine that causes vibrations and noise, which are important factors that influence the high-speed development of looms and decrease their performance. In this work, mechanical factors such as stresses and vibrations were studied for the weaving machine heald frame made from composite materials. The finite element models were constructed using the ABAQUS program for the traditional heald frame made from aluminum as well as for the heald frame made from composite materials. The models were simulated using the operating system conditions of constraints and of applied loads. The composite materials used are carbon fibers and glass fibers. The mode shapes of the models as well as the generated stresses were presented. The results showed a significant improvement in use of the composite materials that can reduce the frame vibration and withstand the generated stresses.

A direct modification of the surface of the basalt fabric was carried out by using magnetron sputtering to obtain composites intended for effective protection against contact and radiant heat. One-layer composite with a coating of aluminum (Al) and zirconium dioxide (ZrO 2 ), two-layer composite with a coating of Al/ZrO 2 , and two-layer composite with a coating of Al/(ZrO 2 + titanium dioxide [TiO 2 ]) were deposited on the fabric surface. Scanning electron microscopy with energy-dispersive X-ray spectroscopy analysis was used to assess the coating on basalt fabrics and determine their chemical composition. Parameters such as thermal conductivity coefficient, resistance to radiant heat, and resistance to contact heat for a contact temperature of 250°C were determined for assessment of the composites from the point of view of protective properties. The similarity analysis of composites was performed to state the impact of coating components’ content and coating thickness on chosen parameters. It was found that a two-layer composite in which the outer layer is Al and the inner layer is a mixture of ZrO 2 and TiO 2 provides good thermal insulation properties. The composites capable of protecting against contact heat at the first efficiency level and against radiant heat at the second efficiency level were obtained.

Numerical simulation basic steps are making a model and recreating the course of the examined process. The article presents numerical modeling of the component of heat flow through a composite developed on the basis of basalt fabric. The composite consisted of the following components: basalt fabric, modified with a composite coating consisting of 1 µm thick aluminum with a mixture of 1 µm zirconia and titanium dioxide, silicone, and Mylar® film modified with the same coating as the basalt fabric. Numerical modeling was performed using the ANSYS 2022 R1 program. The performed numerical simulations of the temperature gradient represented the contact heat resistance test for the contact temperature of 250°C for the basalt fabric and the composite. The proposed model reproduced the exact course and results of the actual study. Each of the layers making up the composite had a thickness and was mapped in accordance with the physical model.

Wide-width weaving machines typically employ the method of increasing the shuttle’s initial speed to achieve a broader weft insertion. However, this approach not only leads to issues such as significant equipment vibrations, high noise levels, increased energy consumption, and reduced lifespan but also has limitations in achieving substantial increases in the fabric width. The article proposes a wide-width weft insertion method based on high-temperature superconducting magnetic levitation technology. It utilizes the levitation characteristics of high-temperature superconducting shuttles in a permanent magnet array’s magnetic field to levitate the shuttle. The shuttle is then propelled by a traveling wave magnetic field generated by an array of electromagnetic coils, enabling wide-width weft insertion. Based on the required thrust values and weaving speed for the shuttle insertion process, the structural parameters of the weft insertion guideway were calculated. A superconducting suspended weft insertion structure was designed, and a mathematical model between the weft insertion guideway and the shuttle was established. Subsequently, a simulation model of the weft insertion guideway was created using Simulink, and the model was simulated, verified, and analyzed using the field-oriented control algorithm. The simulation results indicate that the operating speed of the levitated shuttle and the driving force for weft insertion meet the requirements for high-speed wide-width weaving.

In this study, ultrasound energy was applied to assist the alkali hydrolysis of polyethylene terephthalate (PET) fabric, and then, the results were compared with those of the mechanical oscillating method, which was used as the control. The effects of various factors such as the sodium hydroxide concentration, the dosage of dodecyl dimethyl benzyl ammonium chloride (DDBAC), and the frequency on the weight loss of the PET fabrics were systematically investigated. The surface appearance and microstructures of the treated fibers with different methods were analyzed using a scanning electron microscope and X-ray diffraction, respectively. The results showed that DDBAC played a prominent accelerating role in the hydrolysis of the PET polymer, and the frequency had a great influence on the weight loss of the PET fabric. Ultrasound with a frequency of 60 kHz showed a similar decomposition rate as the control, resulting in similar weight loss, which was the highest value among the three frequencies (20, 60, and 80 kHz). In addition, the application of ultrasonic energy led to more pits on the fiber surface, a smaller average grain size, and decreased crystallinity of the treated fibers, while the mechanical oscillating method resulted in slightly increased crystallinity. By comparing the K/S value of the dyed fabrics with two commercial disperse dyes, we found that the treatment method had no obvious correlation with the color depth of the treated fabric.

Bio-based polyamide 56 (PA56) has significant advantages in reducing oil dependence and reducing carbon emissions. This study compared the physical properties of bio-based PA56 and conventional polyamide 66 (PA66) fibers and their fabrics. The results showed that due to the odd arrangement structure of carbon atoms in PA56 fiber molecules, its crystallinity and orientation were lower than those of PA66. At the same time, PA56 had a higher degradation rate and coloring rate due to its smaller crystallinity and higher moisture content and gave PA56 fabrics better instantaneous cooling and moisture absorption and drying properties. In addition, the molecular structure characteristics of PA56 also lead to a lower stiffness and soft feel of the fabric, which is beneficial for improving the curling phenomenon of the fabric. Overall, bio-based PA56 fibers can meet the applications in the textile and clothing field and can largely replace PA66, which is worthy of further research and utilization.

In the ready-to-wear industry, bias tape is one of the many factors that affect the efficiency of the manufacturing process. In particular, the bias tape change period slows down production. The purpose of this study is to identify the effect of fabric length on the time of changing bias tape rolls. At most manufacturers, the bias tape is made by cutting an average of 1 m from the product’s own fabric. In this study, the effect of bias tape fabrics cut into three different lengths on the manufacturing process was compared with three models. By producing bias tape for each model, the time spent on cutting the fabric, sewing, and changing the roll in the bias holder that feeds the lockstitch machine was calculated. It was revealed that the difference in fabric length affects the efficiency of the sewing process. Namely, it was found that the time spent on changing the bias tape roll decreased between 4.31 and 8.98%. Based on these findings, it can be said that the time efficiency can be increased by increasing the length of the fabric of the bias tape roll to be produced, and thus the production process could be accelerated.

In Poland, the currently used lasts are based on data obtained in the 1970s. These data may be largely out of date, which is due to changes resulting from secular trends, migration changes, and, above all, the fact that there are now tools that enable measurements to be made with significantly higher precision. Such tools are 3D scanners. In this article, we present the results of children’s foot measurements taken using a 3D scanner. We collected data on the feet dimensions obtained with the 3D scanner for boys in the age range of 4–13. We have obtained data on dimensions, proportions, and the rate of changes in consecutive years. The obtained data confirmed the increase in dimensions of the children’s feet as well as changes in proportions. These data will be used for development of new standard for lasts. The aim of the study was to collect anthropometrical data on boys’ feet dimensions.

Standard minute value serves as a pivotal metric guiding the arrangement and balancing of production cycles in clothing production lines, and plays a crucial role in cost pricing and production order arrangement for clothing products. Given the complexity of the garment sewing process, ten influencing factors including fabric weight, fabric thickness, fabric density, stitching length, stitching shapes, cut pieces numbers, notch numbers, sewing technologies, sewing machine, and auxiliary accessories were identified. Upon this foundation, a standard sewing time prediction model, Improved particle swarm optimization - Back-propagation neural network (IPSO-BP), was proposed, focusing on non-quantitative factors. The IPSO-BP model was trained using actual sewing data from a women’s clothing production company. Compared to the unoptimized BP neural network, the IPSO-BP model demonstrated significant advantages in terms of convergence speed and prediction accuracy. Therefore, the IPSO-BP model proposed in this study holds promise for predicting standard sewing hours effectively.

Recently, there has been a sharp increase in interest in Smart clothing. This type of clothing is equipped with electronic systems connected using wires with various types of connectors. This article presents the impact of repeated current switching through contacts made of electroconductive fabrics on their electrical resistance and analyses the influence of selected parameters of these fabrics on the above phenomena. Textile contacts described in the article are one of the most important parts of the future textile electric connectors incorporated into modern Smart clothing. The article also describes tests of resistance of these fabrics to overheating caused by the current flowing through them. The present research was conducted to check the suitability of electroconductive fabrics for making electrical contacts of future textile connectors. The research presented in the article showed that electroconductive fabrics can be used as durable contacts for direct current circuits carrying currents of several amperes. The type of metal with the highest percentage among the metals used to impart electroconductivity to the tested fabrics has a statistically significant impact on the durability of electrical contacts made of these fabrics.

In order to realize the rapid design of warp-knitted jacquard spacer shoe-upper materials and to explore the influence of different fabric surface organization structures on their air permeability, it is proposed to numerically simulate the air permeability performance of jacquard shoe-upper materials using ANSYS fluid analysis. First, four kinds of shoe material specimens with different upper and lower layer mesh alignment relationships are designed and tested, then the corresponding geometric structure models of the fabric are established based on the samples and appropriately processed, and finally the air permeability of the shoe material is numerically simulated and calculated based on computational fluid dynamics. The results show that, under the same conditions, the air permeability of double-sided mesh structure is significantly better than that of single-sided mesh structure, and its air permeability can be optimized by adjusting the relationship between the upper and lower layers of the fabric mesh; the airflow mainly passes through the fabric pores and gaps between the yarns, and the closer the fabric structure is, the more the air flow is hindered, and the worse the air permeability is. The simulation results of the established numerical model are consistent with the measured results, and the error is less than 10%, so it can be used to simulate and predict the air permeability of the warp-knitted jacquard spacer footwear materials, and provide theoretical support for the design and performance research of footwear materials.

The lattice apron-based compact spinning system is a form of pneumatic compact spinning that employs airflow to condense fibres into a bundle, enhancing the yarn’s attributes. To explore the airflow dynamics in pneumatic compact spinning, researchers primarily employ traditional theoretical approaches, experimental measurement techniques, and computational fluid dynamics (CFD) methods. In our previous research, we utilized CFD to observe the airflow patterns in pneumatic compact spinning. In this study, we implemented experimental measurement techniques to assess the impact of a 3D-printed guiding device (B-type) on yarn properties. We tested different fibre types in the condensing zone of the compact spinning system with a lattice apron. We used three types of roving to spin the yarn: pure cotton, cotton/polyester (80/20), and polyester/viscose (65/35). The findings revealed that yarns spun using the guiding device exhibited superior strength, hairiness, and evenness compared to those spun without the device.

Aiming to tackle the issue of virtual fitting, this study proposes an integrated solution encompassing key stages, such as fabric modeling, virtual stitching algorithms, and clothing–body contact mechanisms, with focus on simulating and calculating the clothing pressure. A fabric model based on a particle–spring system is developed, with an emphasis on exploring the relationship between spring coefficients to achieve parametric independence of the virtual fabric. To turn the fabric into clothes, an algorithm for stitch line generation is introduced along with discussions on springs with constraint to improve the rendering accuracy and enhance effects. For simulating the clothing–body contact, a body characterization model consisting of slices is constructed and utilized to compute fabric deformation and its pressure exerted on the human body. Validation tests are conducted by comparing calculated pressures with real measurements obtained from a mannequin, demonstrating an error of 10.9% for the fit size of clothing and below 10% for smaller sizes. These results indicate that the proposed solution not only enables realistic visual effects of virtual clothing but also generates meaningful pressure values based on fabric properties, clothing patterns, and sizes. This lays a solid foundation for the valuable assessment and prediction of clothing pressure in virtual fitting scenarios.

To enhance the intelligence of the ethnic clothing customization industry and provide online solutions for clothing ordering and fashion shows, this study analyses the latest developments in the fields of digital human models, 3D clothing models, and virtual clothing displays in recent years. This study focuses on analysing the categories and processes of three related technologies in clothing virtual display and compares the advantages and disadvantages of four human body modelling methods. Reshaping the facial features of a 3D body scan model and binding the bones of each part is key to providing a personalized body model. In addition, 3D clothing modelling technology is classified into three methods. The 3D fabric scan data are used to establish realistic seam information and process details simulation and use hybrid modelling methods to virtually sew 2D samples, which can enhance the realism of clothing models. The virtual display platform for ethnic clothing is constructed through layered design based on the Unity3D engine, matching versions and virtual display. The above research ideas can solve bottleneck problems in clothing customization. This has important guiding significance for opening up the ethnic clothing customization market, promoting the intelligence of the customization industry, and promoting ethnic clothing culture.

In the present work, seven different weave-structured jute fabrics were treated using an organophosphorus-based flame-retardant (FR) chemical (ITOFLAM CPN) along with a cross-linking agent (KNITTEX CHN) by the pad–dry–cure method. The flammability properties were determined by vertical and horizontal flammability tests and limiting oxygen index (LOI). The flame-spread and after-glow time in the vertical flammability test were calculated to be zero seconds on the FR-treated fabrics while the untreated fabrics were completely burnt. The burn rate in the horizontal flammability test is also measured at zero seconds on the FR-treated fabrics. The highest LOI (43.33) is found in the Twill-3/1 and 4-ends Irregular Satin fabrics, while other fabrics had similar LOI (40) results after FR treatment. The maximum char length (71 and 74 mm) was determined in the warp and weft directions of the Plain-1/1 fabric, while an average minimum char length was found for Twill-2/2 fabrics. Despite the significant improvement in FR performance, it strongly affects the tensile properties of FR-treated fabrics. A substantial loss of tensile strength loss was measured in all treated fabrics; however, the highest loss (77%) was examined for the Plain-1/1 fabric, and the lowest loss of strength (60%) was in the Basket weave (Matt)-4/4 fabric.

The article presents a procedure for assessing and selecting the shape of the ring spinner spindle head that is optimum for yarn manufacturing using the balloonless system, considering multiple criteria. This procedure consists of two stages: the Pareto-optimal method and the distance function method. Twelve spindle head variants were designed and manufactured of 100Cr6 bearing steel composed of C (0.93–1.05%), Si (0.15–0.35%), Mn (0.25–0.45%) along with aluminium alloys EN AW-6060 (AlSi1MgMn) containing Si (0.70–1.3%), Mg (0.6–1.2%), Mn (0.4–1.0%) and EN AW-6060 (AlMgSi) containing Si (0.30–0.60%) and Mg (0.35–0.60%). The shapes of the heads were developed on the basis of the design solutions used previously by the leading ring-spinning machine and spinning spindle manufacturers. Four design variants of spindle heads, made of AlMgSi wrought aluminium alloy, have a unique shape that enables shaping their teeth (notches) by extrusion on a hydraulic press. The assessment criteria were production cost per unit, head weight, maximum surface hardness HV0.1, and four yarn technological quality criteria: maximum yarn tension values during the formation of the base, body and head of the package, and the tension amplitude. The assessment values for the criteria obtained through calculations and measurements were normalized. Then, a set of Pareto-optimal solutions was determined using seven criteria. Due to the fact that this set consisted of six variants, the distance function was used to select the best one. The best design variant of the head is the one corresponding to the lowest distance function value. In our case, the variant is a unique shape, made of AlMgSi alloy, with teeth thickened on the outer diameter of the head, ensuring the lowest yarn tension value at the height during the formation of the package.

Based on the current process of clothing design and development, as well as research and analysis of domestic and foreign literature, this article guides the current digitalization status of the front-end and back-end of the clothing industry and proposes the research problem of this topic. Through clothing design modeling (physical model and design of fabrics, collision detection analysis between human body and fabrics, clothing fabric rendering, and flexible 3D clothing simulation model) and dynamic virtual display of clothing, an effective method to solve the problem is constructed. It has been found that during the design phase, the real effect of clothing fabrics can be realistically restored, and the development speed can be improved, reducing labor costs. At the same time, dynamic simulation display can be used to solve the cost waste problem of sample materials. It can also improve the product selection rate and design level, and solve cost and time problems at the source.

The Turkish textile and clothing (TTC) industries, which are mainly made of small and medium enterprises (SMEs), are the main source of export for the Turkish economy since the end of 1980s. The introduction of digital technologies has changed the competition for the TTC industries and this change has been accelerated after the covid-19 pandemic. Digitalization of SMEs is accepted as a social and technical process in which organizational learning is the main actor and therefore, the aim of this research is to explore the relation between organizational learning, digitalization, and internationalization for TTC industries. A parallel-results convergent mixed method approach in which qualitative and quantitave analysis are performed seperately and integrated later is applied in this research. The data of the research were collected by semi-structured interviews and survey questionnaires, which are analyzed in MAXQDA and analysis of moment structures.

As a material that can release infrared rays, volcanic rock polymer fibers can be used in textiles to improve human microcirculation, which is helpful to relieve chronic inflammatory diseases such as perishoulder arthritis. In this article, there are two different kinds of exterior yarns. Volcanic rock blended polyester, volcanic rock blended polyamide, polyester and polyamide are chosen as the material type of exterior yarn Ⅰ, whereas the material type of exterior yarn II is conductive polyamide yarn. The exterior yarn feed ratio of exterior yarn Ⅰ and exterior yarn II is designed as 8:0, 7:1 and 6:2 when weft plain stitch, 1 + 1 mock rib and 1 + 3 mock rib are used as the knitted structure of the fabric. According to the three-factor four-level orthogonal experimental design method, the sample protocol was established, and 16 knitted sample fabrics were produced. Then, the promotion multiple of blood flow velocity on human epidermal microcirculation of each sample was tested and analyzed. The results show that the promotion multiple of blood flow velocity on human epidermal microcirculation of the fabrics woven by volcanic rock polymer fibers is better than that of the blank control group, and the difference between fabrics with different volcanic rock polymer fibers is small. The higher the proportion of exterior yarn Ⅰ is, the better the promotion multiple of blood flow velocity on human epidermal microcirculation of fabric will be. The effect of knitted structure on the promotion multiple of blood flow velocity on human epidermal microcirculation of fabrics is not obvious. This study provides reference for the design of medical or health textiles for chronic inflammatory diseases.

The helmet shell material featuring a gradient in bending is urgently required for the next-generation integrated helmet system. However, achieving a bending gradient design for orthogonal woven composites on a 3D shell surface is a significant challenge. Here, nonorthogonal woven composites at 30°, 45°, and 60° were fabricated, and their bending properties are discussed. Furthermore, their bending properties are compared to those of plain off-axis woven composites, which indicates that the bending linearity trend of nonorthogonal woven composites is evident. Notably, the bending strength of the 30° and 60° nonorthogonal woven composites is 66.9 and 67.4% higher, respectively, than that of the plain off-axis woven composites, and the bending modulus is 169.8 and 196.9% higher, respectively. Finally, a finite element analysis of the bending properties of nonorthogonal woven composites was conducted, and a stress analysis of the inner layers was also conducted. This work paves the way for designing gradient materials for helmet shells.

Painted during the Yuan Dynasty, Taoist Celestial Beings Worshiping is a Taoist propaganda painting. It is one of the largest surviving ancient murals worldwide, featuring a variety of images of these beings dressed in costumes that vividly illustrate the blend of religious and artistic values in Chinese culture. To record and present the mural more intuitively and improve the study of Taoist Celestial Beings Worshiping, this article takes the example of five goddesses centered Queen Mother of the West in the mural and analyzes the styles, structures, colors, and patterns of the costumes from the perspective of costume engineering. Human models are established and the costumes at multiple levels are reconstruction by means of 3D virtual simulation technology. The display images are accompanied by QR codes, which can be scanned to view the 3D model. Finally, the Fuzzy Analytic Hierarchy Process was used to comprehensively evaluate the reconstruction effect of clothing, and the result was “good.” The resulting digital figure can realize the “revitalization of cultural relics” and provides a new perspective for the digital exhibition of murals, which is conducive to the development of digital tourism and promotes the development of traditional culture.

Most of the sports underwear available is sewn using cutting and sewing techniques. During the exercise process, it is easy to cause discomfort to the skin due to repeated friction at the seam, and at the same time, it is also a waste of manpower and raw material costs. In order to address these issues present in existing sports underwear, during its design and development, combined with fully forming knitting technology, construction process model, so as to realize the integrated knitting of sports underwear. First of all, through the characteristics of the local style of sports underwear, the key points of its prototype were probed. Second, on this basis, its process model was established, including the forming methods and knitting rules of the body, shoulder collar, and bottom circumference. Finally, the feasibility of the technological model is proved by the braiding of a fully formed sports underwear. The change in the body size can be achieved by using the two-side braiding transfer method. The curve contour of the shoulder and neck can be obtained by using the triangular polyline segmentation method. The bottom part is divided into a cylinder part and a supporting part. The local braiding method is used to achieve the knitting. This study puts forward a process model and application method of fully formed sports underwear, which provides a certain method and reference for the design and production of fully formed sports underwear.

The current study aims to explore the representative and typical female body shapes through in-depth observation and analysis of the diversity in Malaysian female body shape characteristics across different ethnic and age groups, which assists in facilitating the establishment of accurate apparel size standards. This study was conducted in Selangor, which is the most populous and developed Malaysian state. The data were collected via a highly systematic approach. The K -mean clustering method was applied to synthesise and analyse the collected data, which classified the body types into five major clusters. The results not only revealed significant differences in the distribution of body shapes across ethnic and age groups but also highlighted the limitations of the various sizing systems currently employed by the Malaysian apparel industry to fulfil the requirements of the diverse Malaysian market. The findings provided practical implications for apparel manufacturers and retailers with concrete evidence to support improved product design and enhance customer satisfaction. A deeper understanding and categorisation of Malaysian females’ body types could also assist the apparel industry in developing more tailored sizing systems. Resultantly, an improved system minimises return rates, optimises inventory management, and supports environmental and sustainability goals by reducing overproduction.

In order to derive the structural properties and deformation behavior of the weft-knitted transfer fabric, a multilayer spring-mass geometric circle model with weft-knitted transfer loop is provided in conjunction with the fabric samples’ image. Eight type-value points were utilized to control the transfer loop’s morphological structure. Connections between the type-value points and the particle system were established. Non-uniform rational B spline curves and texture mapping were utilized to create the three-dimensional impression of the weft-knitted transfer loop. By measuring the offset of the type-value points in conjunction, the actual deformation of the weft-knitted transfer fabric was determined. Utilizing a cylindrical envelope box for collision detection, the possible unreasonable interpenetration phenomenon in the simulation was solved, and thus a stable weft-knitted transfer loop structure was obtained. Using Microsoft Visual Studio and C#, the deformation of the weft-knitted transfer fabric was simulated, the simulated weft-knitted transfer fabric’s deformation pattern accurately depicts the fabric’s three-dimensional structure and deformation behavior while also matching the structural characteristics of the fabric sample. The findings demonstrate that the theoretical structural model of weft-knitted transfer fabric constructed can accurately represent the loop’s structure, and the actual deformation of the simulated weft-knitted transfer fabric is consistent with the deformation characteristics of the fabric sample. Weft-knitted transfer fabric’s deformation behavior may be effectively reflected by the multilayer spring-mass geometric circle model, allowing for the modeling of the fabric’s morphology and 3D structure.

Weft-knitted jacquard plush fabrics are widely used and have a wide variety of varieties, but the design and production process is complicated, time-consuming, and labor-intensive. To reduce the time and cost of fabric sampling and production, a method for designing and simulating these fabrics is proposed based on an analysis of their structural characteristics. Following the design principles of weft-knitted jacquard plush fabrics, mathematical models for pattern design and structural design were established sequentially, leading to the generation of a mathematical model for the knitting diagram. Arrays for raw material editing and threading editing were created to set various parameters. Second, loop models were established based on plush loop shapes, including a forming loop model, a U-shaped loop model, a Henkel plush loop model, a “8”-shaped plush loop model, and a O-shaped plush loop model. Finally, the effects of lighting and number of segments were investigated in THREE.Tube Geometry on the simulation’s effectiveness and speed. By comparing actual fabric images with simulation images, the feasibility of the design and simulation method was verified. This resulted in a computer-aided design process for weft-knitted jacquard plush fabrics, providing an effective method for their design and simulation. The proposed method holds significant theoretical and practical values.

The textile and clothing industry is undergoing a shift towards a circular business model, driven by new European Commission regulations, which mandates that by 2030, textile products available on the European Union (EU) market must be recyclable and sustainable. To facilitate data collection, storage, and sharing throughout the entire product lifecycle and ensure product traceability and sustainability, the use of Digital Product Passports (DPPs) will be required. This article presents an analysis of the most commonly known digital data technologies from the perspective of their use in digital garment labelling, describing their advantages and limitations. The analysis is complemented by practical insights gathered from semi-structured interviews with garment producers in the Baltic Sea region. The survey revealed that producers prioritise sustainability and are prepared to digitise product information but are awaiting EU’s clear guidance. Despite the challenges posed by DPP implementation from the global, producer, and customer perspectives, upcoming regulations are seen as providing new competitive opportunities for products and services. Both the technology analysis and the expert survey indicate that QR (quick response)-based smart tags are potentially the most straightforward solution for the initial phase of DPP implementation.

Textile industry has a significant water footprint (WF), leading to various sustainability challenges. This article discusses key findings on the WF and outlines potential solutions. The industry’s WF includes three types: green, blue, and grey. Textile manufacturing is water-intensive, with stages like pretreatment, dyeing, printing, and finishing. This can contribute to water scarcity in some regions. Water pollution is another critical challenge, as the industry generates considerable wastewater containing diverse pollutants which can harm ecosystems and pose risks to public health. Different treatments to reduce the pollutants in water are studied. We have grouped innovations into five major categories for water conservation efforts in the textile industry: To address these sustainability challenges, several solutions are proposed. Each category offers a pathway to reduce its environmental footprint through water conservation. The adoption of water-efficient technologies, such as low-water dyeing and wastewater recycling, can reduce water consumption. Stricter policies for pollution control, along with incentives for sustainable practices, can encourage industry-wide change. Collaboration among stakeholders, including industry, government, and environmental groups, is also crucial for promoting sustainability and reducing the industry’s environmental impact. These approaches can help the textile industry move toward a more sustainable future. Further research needed is suggested.

The clothing industry is often perceived, particularly in the European context, as a declining, traditional, labour-intensive industry. Nonetheless, in recent years in Poland, after over three decades of steady shrinkage, though the average scale of operations has continued to decline, the number of firms in the sector has been much more stable. In their analysis of the locations of apparel producers on the national level, the authors point to the changing geography of the sector in terms of its increased or diminishing relative presence in some areas. The links between location tendencies among firms in the clothing industry and other fashion-related institutions and initiatives are noted, as are new firms in the creative sector. The spatial patterns observed point to the ability of the resized sector to leverage emerging market opportunities and upgrade selectively, and to its broader evolution from a traditional towards a creative industry.

This research endeavors to analyze the dynamic characteristics of the dobby, particularly the influence of a modulator on the dynamic response of the heald frame. By constructing precise kinematic and dynamic mathematical models and employing efficient computational algorithms, this study delves into the motion behavior of dobby. Component elastic deformation is considered, and a detailed analysis of the heald frame’s vibrational properties is conducted. With the establishment of dynamic and kinematic equations, coupled with Taylor series expansion and partial derivative techniques, the displacement errors were accurately calculated. The implementation of the fourth-order Runge–Kutta method facilitated numerical simulation, allowing for the analysis of the effect of cam profile errors on vibrational characteristics. The findings indicate that cam profile machining and system errors significantly influence the vibration amplitude under high-speed conditions. Consequently, this research highlights the imperative to control operating speeds in the design and operation of dobby and enhance vibration stability through precise machining of cam profiles, using high-precision equipment, and regular maintenance, which are essential for optimized design and improved stability and reliability.

The quantitative determination of wool and cashmere mixed fiber is an indispensable quality control link in the textile industry, crucial for improving international trade status, ensuring product quality, and safeguarding consumer rights. Therefore, the goal of this study is to develop a reliable method for estimating fiber contents in wool–cashmere blends based on near-infrared (NIR) spectroscopy. A total of 210 mixed samples of 21 different proportions of cashmere and wool are prepared in the experiment, and data are collected in the NIR spectral band of 1,000–2,500 nm. Convolution Savitzky–Golay (S–G) combined with the second-order derivative is then used for spectral preprocessing. The variable iterative space shrinkage approach (VISSA) optimizes the characteristic wavelengths, and 339 wavelength points are selected. The prediction model of the least squares support vector machine (LSSVM) is established by particle swarm optimization (PSO), fast positioning, and analysis of key information related to the target in complex spectral data. Finally, the training set and the prediction set are divided according to the ratio of 8 : 2. Experiments show that in terms of modeling and prediction, the PSO-LSSVM model based on the wavelength selected by VISSA has a prediction determination coefficient R-squared of 0.9821, a prediction root mean square error of 1.1263, and an mean absolute error of 0.6527. The hybrid modeling method of VISSA, PSO, and LSSVM based on NIR spectroscopy (VISSA–PSO–LSSVM) can provide a more accurate and stable method for the non-destructive detection of cashmere and wool blended fiber content.

The shortcomings of traditional pile fabric design and simulation in simulating clustered structures are addressed in this study by proposing a new three-dimensional (3D) simulation method. To accurately capture the details of clustered pile fabrics, a fine geometric model of a single pile loop is first established, and a novel geometric transformation algorithm, combined with rotational transformations and trigonometric calculations, is employed to achieve the natural aggregation of pile fibers, resulting in a highly realistic clustered structure. Additionally, to enhance design flexibility and accuracy, a pile design pattern is introduced, and for the first time, a Depth-First Search (DFS) algorithm is utilized for precise pattern recognition and determination of the directions of pile fibers, effectively solving the challenges of clustered area identification. To enhance the visual realism of the simulation, the Phong illumination model is adopted to simulate the lighting effects on the fabric surface, and blurring processes are applied to eliminate sharp edges and noise, resulting in a softer and more natural simulation output. Based on the recognition results from the DFS algorithm, the directions of the pile fibers are finely adjusted to achieve a realistic simulation of clustered pile fabrics. Experimental validation demonstrates that the proposed method produces 3D simulation results that closely resemble actual pile fabrics, demonstrating significant practical value and innovation.

A finite element analysis model was employed to analyze the heat conduction behavior of glass fiber/metal (stainless steel, aluminum, or oxygen-free copper) composite materials under a constant thermal load of 100°C on the metal surface, i.e., the temperature distribution after reaching thermal equilibrium. By comparing and analyzing the effects of different metal materials, different air convection heat transfer capabilities, and different metal phase thicknesses, the heat transfer mechanism is elaborated. The results indicate that the metal with stronger heat conduction capacity induces more uniform temperature distribution, while the temperature uniformity on the fiber is relatively worse. Besides, with the increase of the air convection heat transfer coefficient, the temperature on the fiber phase shows a significant downward trend, however, the impact on the metal phase remains limited. In addition, the metal thickness primarily affects the weight or rigidity of the composite material, with minimal impact on temperature distribution.

Consumers recognize the appearance and texture of fabric through viewing photographic images on E-commerce. However, the relationship between evaluations of the actual fabric and its image remains unclear. To understand the evaluation difference between actual fabric and its image, we investigated the relationship of visual evaluations including the price evaluation between actual white fabrics used for dress shirts and their photographic images concerning the online purchase of items presented by their photos. Participants evaluated the impressions of 24 white fabrics (actual fabrics and their images), comparing them with a standard white fabric. Participants also estimated the prices of shirts hypothetically made from different fabrics. We compared the difference between the results for actual fabrics and images. We also carried out a principal component analysis of those impressions and examined the relationship among principal component analysis results, weave structure, and fabric materials and price estimation. In a comparison of actual fabric and image evaluations, the impression of glossiness and brightness differed, with the actual fabrics being rated significantly higher in terms of glossiness and brightness. These differences are due to the difference in media (i.e., direct viewing versus screen display), although the visual environment of the lighting and displays may have had an effect. In principal component analysis, the first principal components were Delicateness and Glossiness for both actual fabrics and their images. The second principal components were Lightness and Coolness for the images of fabrics and Lightness, Coolness, and Softness for the actual fabrics. Fabrics evaluated highly in the first principal component had high price estimations. Thus, it is clear that Delicateness and Glossiness affected the price evaluation for both actual white fabrics and their images. Fabrics with a high value of Delicateness and Glossiness were a poplin made of at least 95% cotton. In contrast, fabrics containing linen and having a small repeating dobby pattern with roughness were evaluated as having low Delicateness and Glossiness and were assessed at a lower price. Additionally, even in the case of blended fabrics such as a cotton–polyester fabric, the expected price was high for diagonal patterns such as stripes and checks. These results will be helpful in the procurement of fabrics with which to make clothing and in the marketing of clothing for E-commerce.

The article concerns the study on multidirectional drape and bending rigidity of six wool (clothing) fabrics with two types of adhesive inserts. The aim of research was to investigate the effect of joining woolen fabrics with “Freudenberg Vilene” adhesive inserts on the bending rigidity and multidirectional drape. The adhesive inserts were differentiated according to mass per square meter, while the fabrics were differentiated according to thickness, weave, and mass per square meter. Based on the scientific literature, the issues related to the methods of testing the bending rigidity and multidirectional drape coefficient were discussed. All the conducted tests were aimed at the proper selection of adhesive inserts for the designed clothing products. The use of adhesive inserts affects the bending stiffness and multidirectional drapeability of clothing material. The fabric weave significantly affects the values of bending rigidity and drapeability. As the thickness of adhesive inserts increases, the overall bending rigidity increases. The greater the fabric mass per square meter, the stiffer the fabric. As the mass per square meter and thickness increase, the multidirectional rigidity of fabrics increases. The value of bending rigidity for the plain fabric is higher compared to twill fabric.

The relationship between the speed of the driver plate and the collision of the spindle and the track is studied in this work. It is theoretically analyzed that the spindle will collide with the track in different degrees in the process of motion, and the impact is more intense due to the vibration of the mechanism. First, the dynamic equation of the spindle-track model is established. Then, fireworks algorithm is used to optimize the speed of the driver plate, to reduce the collision and impact times of the spindle on the track, so as to reduce the severe collision times between the spindle and the track, resulting in the wear of mechanical parts and affecting the braiding effect. Finally, it is concluded that the number of collisions increases sharply with the increase in recovery coefficient when the random disturbance is not considered; second, the number of collisions decreases with the appropriate increase in friction coefficient when the random disturbance is not considered; and third, the number of collisions increases sharply with the increase in random disturbance.

This article presents a comprehensive numerical and experimental analysis of the ballistic performance of soft bulletproof vests designed for women. The study involved a woman aged between 24 and 28 with a breast size of 85C. Two ballistic packages made from Twaron ® CT 709 fabric were designed and constructed for her, featuring cut-and-sew formed breast cups and differing significantly in the number of layers (16 and 30 layers). The impact of the number of layers on breast deformation during the shooting was analyzed using numerical modeling and experiments, which included a Parabellum 9 mm × 19 mm FMJ ® bullet and a Roma No. 1 plasticine substrate formed based on a plaster cast representing a woman’s figure. The research found that even significantly increasing the number of layers in the ballistic package did not lead to a substantial reduction in breast deformation during shooting. The likely reason for this is the cut-and-sew formed breast cups in the ballistic package, which easily undergo transverse deformation upon bullet impact. This suggests a need for further research to optimize the design of protective cups, which are crucial for proper force distribution and minimizing injuries during bullet impact. The conclusions drawn from this study could contribute to the development of more advanced and effective soft ballistic protection solutions for women.

Dyeing plays a vital role in the textile industry, however, associated health and environmental issues have raised significant concerns regarding the types of dyes used. Among these, natural dyes, particularly those derived from plants, exhibit superior safety and environmental performance, making them a more sustainable alternative. Moreover, fabrics dyed with plant dyes can acquire diverse functional properties, including antimicrobial characteristics, attributed to various active ingredients present in plants during the dyeing process. With increasing environmental consciousness and the rising demand for functional fabrics, natural plant dyes have garnered growing attention. In our research, a systemic review of the antimicrobial properties of plant dyes in the textile field was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses method. A literature search was executed through the PubMed and Web of Science databases, from which 132 articles were selected. The results indicate that the overall number of publications in this field is on the rise, especially showing a significant increase in the past 7 years, demonstrating substantial research value and potential. Furthermore, this study conducted an analysis of the content included in the literature, summarizing the different standards and characteristics of antimicrobial testing, with a focus on revealing the antimicrobial mechanisms of plant dyes. It also discussed the mordants and other treatment methods that can effectively enhance the antimicrobial properties of plant dyeing. Building on this foundation, this review discusses the advantages, application potential, and future research directions of antimicrobial natural dyes derived from plants. Through this review, relevant researchers can gain a clearer understanding of the current state and development trends of plant-based natural dyes in terms of antimicrobial properties, thereby promoting further exploration in this field.

The mechanical properties of seaming stitch have been frequently reported. However, the frictional characteristics of seaming stitch have long been ignored. In this article, to reveal the influence of sewing process on the fabric’s friction, we measured the coefficient of friction (COF) of fabric with different seam patterns. These seam patterns were fabricated by using controllable sewing thread and sewing process. On the basis of our experiment, we found that the COF of fabric’s front was higher than that of fabric’s back. Another conclusion is that the COF in the weft direction was higher than that in the warp direction. Additionally, thin sewing thread, long stitch, and large seam space can cause low COF. On the contrary, relative high COF is generated by thick sewing thread, short stitch, and small seam space. According to our results, we expect to provide the matching suggestion between the fabric and seam pattern from the point view of trichology.

Fabric strength plays a crucial role in determining and influencing all other performance attributes of textiles. Therefore, considering the strength of the fabric becomes essential when choosing the appropriate textile for a specific purpose. This article presents an experimental study that focusses on the properties of 100% polyester fabrics. To conduct this study, we created ten fabrics with different weave structures, resulting in a total of 200 samples for tensile strength testing. Moving on to the second phase, we analysed the physical and constructional characteristics of the fabrics, including the number of warp and weft threads, warp and weft density, and weight. This analysis was carried out based on the weave structures. Additionally, we performed tensile strength tests in both warp and weft directions to examine the mechanical properties of the fabrics. Finally, a statistical analysis was performed to determine the impact of the weave structures on the tensile strength of the fabrics.

Optimization of fabric’s mechanical properties, such as strength and bagging deformation of worsted fabrics, is considered one of the most important cases in relation to the use of stenter machine. Because, in this machine, for providing fabric’s dimensional stability with drying and stretching operations, fundamental changes would occur in these properties. Therefore, in the present study, the mechanical properties of the fabric in stenter machine were optimized through simulation of laboratory conditions as well as simulation by the finite element method. First, using laboratory stenter, the experiments were performed on six common worsted fabric samples by the Design Expert software through changing temperature, percentage of fibers, and weight of the fabric, which were considered as the most effective factors. Then, the changed conditions were determined by the central composite design for optimization. For performing the finite element simulation, the initial design was first created using TexGen software and then, the strength and bagging deformation model was investigated by Abaqus software. The results of the simulation showed a statistically acceptable relationship between actual and practical conditions.

The cluster of small- and medium-scale garment industries in Aba and Onitsha positioned Nigeria to meet her garment needs. Regrettably, the production process is encumbered with manufacturing waste, which hinders competitiveness with their international counterparts. This study identified manufacturing waste in the garment production process in the garment industries in Aba and Onitsha with the view of improving the production performance. A survey research design with the use of a closed-ended questionnaire was used for data collection. In total, 372 questionnaires were administered, and 324 were completed and returned, representing 87% response rate. Descriptive statistics such as mean weighted scores was used to analyze the data for this study with the Statistical Package for Social Sciences, version 16. The result of the investigation revealed that unnecessary motion, overprocessing, inventory, waiting, and defects constitute major lean manufacturing wastes in the garment production process. Therefore, concerted efforts must be intensified by the garment industry to eliminate the identified waste with a view of ensuring the garments are competitive with foreign garments.

This study introduces the results of an optimization study on sol–gel application conditions applied to obtain multifunctional (water repellent/flame retardant) denim fabrics using the Design Expert software and a step-by-step approach. The study started by obtaining the proper drying/condensation parameters and water-repellent additive amount, followed by determining the proper co-precursor and flame-retardant additive amount, and finally covering the mechanical tests of the samples to determine if the results would be applicable for industrial purposes. The results indicate that it is possible to approach the optimum process conditions applicable to industrial-scale working conditions to produce denim fabrics with high levels of water repellency and flame retardant performance.

This study proposes a novel drape test method for fully formed knitted flared skirts, specifically tailored to account for the three-dimensional (3D) morphology of the human body. The objective is to accurately assess the drape characteristics of such skirts by developing a comprehensive testing approach. First, a 3D human body model in multiple postures was created using 3ds-Max modeling software and then printed with a 3D printer to serve as a customized test stand. The design and knitting principles for the fully formed flared skirt were examined, and samples were produced using a Shima Seiki four-needle bed computerized flat knitting machine. After fitting the skirt samples onto the 3D-printed human model, drape characteristics were measured with a YG811 drape tester. Using 18 sample skirts, the drape data were analyzed with SPSS26.0 software, revealing that the 3D-printed human model method allows for precise measurement of the drape in fully formed knitted fabrics. This approach offers a more realistic and accurate assessment of drapes, contributing valuable insights for textile design and evaluation in knitted garment production.

Application of models for supplier assessment and selection in the clothing industry remains relatively underexplored. To fill this gap, this research study introduces the following fuzzy hybrid models for evaluating and selecting suppliers for clothing manufacturing firms: fuzzy set theory, Analytic Hierarchy Process method–fuzzy-Technique for Order of Preference by Similarity to Ideal Solution (AHP–fuzzy-TOPSIS), AHP–fuzzy-Weighted Sum Model (WSM), and AHP–fuzzy-Weighted Product Mean (WPM). Criteria weights were established utilizing these models, which were applied to identify the optimal supplier. A practical study was conducted within a clothing firm to evaluate the effectiveness of these fuzzy hybrid models. The main results reveal that the AHP–fuzzy-TOPSIS model outperforms the AHP–fuzzy-WSM and AHP–fuzzy-WPM models in selecting the optimal alternative. Indeed, this approach has the potential to be adapted to different industrial sectors, considering the specific criteria and conditions that govern their supplying processes.