Abstract In order to reduce the development cost of open topping-on structured crochet fabrics and realize the diversified design and three-dimensional (3D) simulation of fabric, the weaving process and principle of this kind of fabric were deeply studied, and the lapping motion and yarn threading motion models of fabric structure were established. Combined with the structural characteristics of fabric, the geometric models of pillar stitch organization, weft lining organization, open topping-on organization, and fringed weft-insertion organization were established under ideal conditions. Through the measurement and analysis of the actual fabric, the number and position of the coil type value points are further determined. The shape transformation of the fringes is realized by combining the random geometric transformation algorithm. This work introduces the structural characteristics and process design method of a typical fabric, and explores the diversified combination of structures, and finally realizes the 3D simulation of fabric with the help of JavaScript and C# computer programming language. The results show that, through 3D simulation technology, we can quickly try different patterns, materials, and color combinations, so as to see the design effect intuitively. This way of virtual display and iterative modification can significantly improve the design efficiency, and greatly reduce the trial and error cost and time consumption, providing an efficient way to find the best design scheme.

Abstract To develop distinctive elastic fabrics, it is essential to produce new elastomeric yarns that differ from conventional elastane filaments. The elastomeric staple yarns examined in this study are composed of poly(ether-ester), or PEE, featuring a chemical structure with an 80/20 weight ratio of a rigid segment of poly (butylene terephthalate) (PBT) and a flexible segment of poly (oxytetramethylene). Initially, staple fibers were created from this elastomeric PEE along with a 25% PBT blend by weight, followed by the production of elastomeric yarns from pure elastomeric staples and blended staple fibers of cotton or poly (ethylene terephthalate) using ring and compact spinning techniques. This study provides a comprehensive overview of the manufacturing process for elastomeric yarns derived from these elastomeric staple fibers. The fundamental mechanical characteristics of the produced elastomeric yarns, such as tenacity, modulus, breaking extension, and elastic recovery, were evaluated and detailed in relation to yarn composition (blending ratio). The most significant feature of high elastic recovery (exceeding 90%) at 10–15% extension is anticipated to facilitate the creation of numerous new types of stretchy materials.

Abstract One of the major issues in the textile industry’s supply chain logistics is transportation, specifically cost, efficiency, and delivery timeframe. This study investigates using the Ant Colony Optimization (ACO) algorithm as a promising method of transport optimization in textile industry logistics. The ACO model uses the same mechanisms as the ants; it considers using more than one distribution point, including many important factors such as distance and fuel. We will elaborate on the entire framework of ACO, with particular emphasis on updating the rules of pheromones and virtual ants’ decision-making process. This study illustrates the application of the ACO model in textile logistics, employing case studies and computer modeling, leading to more significant cost savings and improved service levels in the industry. In practice, the ACO theory improves the supply chain’s transportation efficiency, flexibility, and environmental sustainability, giving the textile industry a competitive edge in emerging markets.

Abstract This article presents an experimental study on the influence of various parameters on sewing thread consumption. Four knitted samples, featuring different structures and thicknesses, were tested by sewing two- and three-layer using chain stitch type 401. This work allows for examining the effects of the sewing machine foot pressure height, surface mass, fabric thickness, and number of layers sewn on thread consumption. It was concluded that lower foot pressure results in a significant increase in the amount of thread used. In addition, accurately predicting thread consumption makes it easier to control the stock level of inventories, which is important for effective supply chain management. With optimized inventory, companies will save on storage expenses and minimize the downtime between operations, resulting in increased productivity. The combined application of neural nets and statistical techniques increases the accuracy of forecasts, which is essential for manufacturers in a highly competitive environment.

Abstract The widespread use οf detergents in the textile industry has raised cοncerns regarding their adverse effects οn the envirοnment and human health. This study prοpοses an innοvative apprοach tο address this issue by develοping a naturally sοurced surfactant. The surfactant was extracted frοm Mesembryanthemum crystallinum (GH) and Salsοla vermiculata (F) by maceratiοn under different time and temperature conditions. The results demοnstrated the high efficiency and detergent efficacy οf the extracts studied. GH, F exhibited the superiοr fοaming capacity reaching 48.51%, stability up to 60 min, and a wetting time up tο 5 min at 25°C. Mοreοver, GH and F detergency capacity is cοmparable tο that οf the reference prοduct. These findings suggest the pοtential applicatiοn οf GH and F as sustainable and envirοnmentally friendly cleaning agents in the field οf textile.

Abstract Near-infrared (NIR) spectroscopy is essential for distinguishing cashmere from wool. It is fast and non-destructive. Both cashmere and wool contain keratin. Their NIR spectral images are very similar. This makes it hard to tell them apart. This article proposes a method to identify and classify two similar fibers. It uses NIR spectroscopy combined with chemometrics. The chemometrics model mainly uses sparse representation and an improved AdaBoost classifier. The sparse representation is used for feature extraction. It expands the distance between sample spectra. This strategy first standardizes the dataset. It then uses the K-singular value decomposition algorithm to learn a low-dimensional dictionary. Finally, it maps the spectra using the dictionary. This approach creates a low-dimensional positive–negative distribution of sample features. It aims to widen the gap for later classification. Also, due to the many cashmere and wool species, some intra-species gaps are larger than the inter-species ones. This has increased misclassification errors. This article uses AdaBoost to assign weights to samples of different species. It optimizes these weights with many decision tree (DT) classifiers. It then uses the sparrow optimization algorithm. It finds the best number and depth of DTs. In the comparison experiments of this article, the sparse representation can effectively amplify the gap between cashmere and wool than principal component analysis and independent component analysis, and the classification efficiency of AdaBoost is also higher than the classification efficiency of K-nearest neighbors, Random Forest, and other classifiers. The combination of these two algorithms can achieve a classification accuracy of 97.4%, which can effectively classify cashmere and wool fibers.

Abstract Integrating electronic components into smart textiles revolutionised the field, with snap fasteners often serving as electrical connectors. This study investigated the electrical and mechanical durability of sewn-on snap fasteners under cyclic fastening–unfastening and interruption of direct current (DC) flowing through them. The available literature indicates that snap fasteners can endure repeated mechanical stresses; however, there is a lack of data regarding their behaviour during the cyclic interruption of DC flow. This research fills this gap by analysing changes in electrical resistance and unfastening forces over 10,000 cycles of current interruption. Results indicate that larger snap fasteners offer greater mechanical resistance, although size does not significantly impact electrical durability. For example, the average force needed to release the snap fasteners after 10,000 cycles is reduced to 5 N for large snap fasteners and 2 N for the small ones. This article also discusses how the substrate fabric and the type of thread used to attach the snap fastener affect the electrical strength of the tested connector. The findings presented offer valuable insights for designing and selecting materials in future smart textile applications, thereby enhancing the robustness and functionality of wearable electronics.

Abstract To investigate the influence of materials on the surface morphology and compressive performance of honeycomb structural components prepared by stereo lithography apparatus (SLA) technology, three typical materials, namely Dutch State Mines (DSM) 8000, Somos® Taurus, and FS 3400GF (Glass Bead Filled Nylon Powder), were selected as raw materials for printing honeycomb structure via SLA. FS 3400GF can withstand a maximum compression force of 14.1 kN in vertical compression, while it is 10.1 kN for DSM 8000 and 5.8 kN for Somos® Taurus, indicating that FS 3400GF bears significantly higher vertical pressure. The maximum force bore by FS 3400GF under lateral compression is 0.47 kN, DSM 8000 is 0.56 kN, and Somos® Taurus is 0.17 kN, suggesting that the lateral compression failure is highly likely to occur. The mechanical compression failure reveals the physical properties of honeycomb structures and provides an experimental support for expanding the potential functional application of honeycomb structures in additive manufacturing.

Abstract The research presented in this article concerns the modeling of physical processes occurring in protective clothing that determine the ergonomics and thermal balance between its user and the work environment. In the first part, three-dimensional models of real composites based on cotton fabrics and aerogel were designed using the original method of Parylene C deposition in the chemical vapour deposition (CVD) process, which have potential application in thermal protective gloves. The models included geometric parameters of real textiles calculated based on high-resolution X-ray tomography. This technique also allowed for the accurate determination of the porosity of the tested materials and the inclusion of the exact air content in the models without the need to reproduce the complex geometry of fibers in the fabric and microgranules in the aerogel. The results of heat transfer simulations performed using the finite volume method, correlating with the results of the experiment verifying them using thermography, showed that the designed models allow for the prediction of heat transfer with high accuracy despite the use of a lot of simplifications in the geometry. The differences between the modeling results and the experiment range from 0.7 to 5.5% depending on the complexity of the model geometry.

Abstract Determination of abrasion resistance of textile fabrics is one of the important parameters describing textile durability, especially utility properties. Currently, used test methods for determination of abrasion resistance are based on organoleptic examination. The end point of the abrasion resistance test carried out for textile fabrics is described in the form of criteria in the standard. The identification of the end point requires manual observation of the sample’s surface. This process is labour and time-consuming and requires a lot of experience. The article presented a new instrumental method for assessing abrasion resistance. The method, based on image analysis techniques, allows identifying the end point of abrasion test without a constant examination of sample surface, without constantly examining the sample surface. The method presented for abrasion resistance assessment involves evaluation of brightness profiles taken from sample scans. The new method, subjected to precision experiments, has shown a good level of repeatability and reproducibility. The instrumental method, together with end point criteria for single thread, could support operators during breakage identification test significantly, shortening the test time and labour consumption.