Search Results (34)

Protective garments for the medical radiation shielding of healthcare professionals must ensure flexibility and shielding performance. As such, process technologies for density enhancement are required when manufacturing shielding sheets to ensure the reproducibility of flexibility and shielding performance. Although previous efforts commonly reduced particle size to minimize porosity, nanoparticle production cost is significant. Therefore, this study aimed to improve the density of the shielding sheet by controlling the spacing between internal particles. The proposed improvement method is based on polydisperse particle packing. Particle sizes can be adjusted using process techniques such as sintering, pressing, and mixing. The study materials used are tungsten and bismuth oxide (eco-friendly alternatives to lead), with polyethylene as the polymer matrix. First, the shielding performance improved by 4% in the sintering process when the tungsten content reached 90 weight percent (wt%). The solvent removal process, used to eliminate the solvent added for polymer utilization, increased the density by 13.18%; however, it was lower than that of the compression process. The shielding performance improved by approximately 10% in the compression molding process when the tungsten content was 90 wt%. This study confirms that optimizing density enhancement strategies for radiation shielding materials can significantly improve shielding performance. Full article

The problem of textile waste generated in production processes poses new challenges for manufacturers. For this reason, an approach to clothing design has been developed that takes into account aspects of sustainable development and the zero-waste concept. The paper presents the development of “T” and “X” silhouettes for women’s dresses according to the proposed new method. The existing basic cuts of women’s dresses were modeled to obtain “T” and “X” basic silhouettes for women’s dresses, and we compare the reduction in losses between the cuts using the newly proposed TAXI method and the TAXI method according to the proposed design. The use of pattern losses based on the pattern of the basic dress cut provides innovative design solutions according to the TAXI method by applying structural elements that adjust the shape of the basic silhouettes of women’s dresses. Fabric utilization using the basic “T” silhouette cut model is reduced to 75%. The TAXI method improves fabric utilization, achieving 75% fabric use with the basic “T” silhouettes and up to 99.8% with modifications. The fabric utilization of the basic “X” silhouette according to the proposed TAXI design method is 99.8%, which is 32.5% higher than the fabric utilization according to the basic pattern. With this comprehensive concept based on the principles of sustainability, the proposed TAXI design method has been adapted for the maximum possible fabric utilization, esthetic quality and fit, while retaining the recognizable silhouette of the garment. Full article

Regenerated cellulose fibers are a highly adaptable biomaterial with numerous medical applications owing to their inherent biocompatibility, biodegradability, and robust mechanical properties. In the domain of wound care, regenerated cellulose fibers facilitate a moist environment conducive to healing, minimize infection risk, and adapt to wound topographies, making it ideal for different types of dressings. In tissue engineering, cellulose scaffolds provide a matrix for cell attachment and proliferation, supporting the development of artificial skin, cartilage, and other tissues. Furthermore, regenerated cellulose fibers, used as absorbable sutures, degrade within the body, eliminating the need for removal and proving advantageous for internal suturing. The medical textile industry relies heavily on regenerated cellulose fibers because of their unique properties that make them suitable for various applications, including wound care, surgical garments, and diagnostic materials. Regenerated cellulose fibers are produced by dissolving cellulose from natural sources and reconstituting it into fiber form, which can be customized for specific medical uses. This paper will explore the various types, properties, and applications of regenerated cellulose fibers in medical contexts, alongside an examination of its manufacturing processes and technologies, as well as associated challenges. Full article

Cotton fabrics with zinc oxide (ZnO) coating are of significant interest due to their excellent antibacterial performance. Thus, they are widely in demand in the textile industry due to their medical and hygienic properties. However, conventional techniques used to deposit ZnO on fabric require long processing times in deposition, complex and expensive equipment, and multiple steps for deposition, such as a separate process for nanoparticle synthesis and subsequent deposition on fabric. In this study, we proposed a new method for the deposition of ZnO on fabric, using cathodic cage plasma deposition (CCPD), which is commonly used for coating deposition on conductor materials and is not widely used for fabric due to the temperature sensitivity of the fabric. The effect of gas composition, including argon and a hydrogen–argon mixture, on the properties of ZnO deposition is investigated. The deposited samples are characterized by XRD, SEM, EDS, photocatalytic, and antibacterial performance against Staphylococcus aureus and Pseudomonas aeruginosa bacteria. It is observed that ZnO-deposited cotton fabric exhibits excellent photocatalytic degradation of methylene blue and antibacterial performance, specifically when a hydrogen–argon mixture is used in CCPD. The results demonstrate that CCPD can be used effectively for ZnO deposition on cotton fabric; this system is already used in industrial-scale applications and is thus expected to be of significant interest to garment manufacturers and hospitals. Full article

Electronic textiles (e-textiles) are a branch of wearable technology based on integrating smart systems into textile materials creating different possibilities, transforming industries, and improving individuals’ quality of life. E-textiles hold vast potential, particularly for use in personal protective equipment (PPE) by embedding sensors and smart technologies into garments, thus significantly enhancing safety and performance. Although this branch of research has been active for several decades now, only a few products have made it to the market. Achieving durability, reliability, user acceptance, sustainability, and integration into current manufacturing processes remains challenging. High levels of reliability and user acceptance are critical for technical textiles, such as those used in PPE. While studies address washing reliability and field tests, they often overlook end user preferences regarding smart textiles. This paper presents a narrow fabric-based e-textile system co-developed by engineers, garment and textiles’ manufacturers, and firefighters. It highlights material choices and integration methods, and evaluates the system’s reliability, sustainability, and user experience, providing comprehensive insights into developing and analyzing e-textile products, particularly in the PPE field. Full article

More than a third of microplastics in surface waters are formed by microplastics released from textile products containing textile fibers (fibrous microplastics). A large amount of fibrous microplastics enters the environment during textile production and the first few washing cycles. Mechanical, thermal, chemical, and biological damage to textiles causes the generation of fibrous microplastics. Textile manufacturers, dyers and finishers, garment producers, distributors, or consumers contribute to this process. During the construction of textiles, multiple issues need to be addressed simultaneously. They are related to the optimization of technological processes and the construction and functionalization of fiber structures, considering ecological requirements, including suppressing the formation of fibrous microplastics. This research is focused on the specification of reasons for the generation of fibrous microplastics during textile production. The influence of the structure of fibers, abrasive deformations, and surface structure of fabrics on the generation of fibrous microplastics is discussed. The release of fibrous microplastics during washing is mentioned as well. Full article

This study explores previous research efforts concerning prediction models related to the textile and polymer industry, especially garment seam strength, emphasizing critical parameters such as stitch density, fabric GSM, thread type, thread count, stitch classes, and seam types. These parameters play a pivotal role in determining the durability and overall quality of denim jeans based on cellulosic polymer. A significant focus is dedicated to the mathematical computational models employed for predicting seam strength in five-pocket denim jeans. Herein, the discussion poses the application of AI for manufacturing industries, especially for textile and clothing sectors, and highlights the importance of using a machine learning prediction model for sewing thread consumption, seam strength analysis, and seam performance analysis. Therefore, the authors suggest the significant importance of the machine learning prediction model, as future trends anticipate advancements in AI-driven methodologies, potentially leading to high-profile predictions and superior manufacturing processes. The authors also describe the limitation of AI and address a comprehensive model of risk outlines of AI in the manufacturing-based industries, especially the garments industry. Put simply, this review serves as a bridge between the realms of AI, mathematics, and textile engineering, providing a clear understanding of how artificial-neural-network-based models will be shaping the future of seam strength prediction in the denim manufacturing landscape. This type of evolution, based on ANN, will support and enhance the accuracy and efficiency of seam strength predictions by allowing models to discern intricate patterns and relationships within vast and diverse datasets. Full article

This research paper presents an all-encompassing methodology for multi-criteria decision-making in the apparel sector, with the particular objective of aiding in the determination of the most appropriate location within the CLMV subregion. The research is conducted in three crucial stages. The process began with the administration of a survey to proprietors of garment businesses in both Thailand and the CLMV countries. This survey resulted in the compilation of an exhaustive list of site-selection criteria and sub-criteria. Based on the findings of subject matter-expert interviews, Cambodia (C), Vietnam (V), and Myanmar (M) were identified as feasible alternatives. Subsequently, the questionnaire criteria and sub-criteria were evaluated utilizing the Fuzzy Analytic Network Process (Fuzzy ANP), which involved the utilization of meticulously designed pair-wise comparison matrices and local priorities. Five specialists from the Thai entrepreneurial community affirmed the effectiveness of Fuzzy ANP and expressed interest in expanding manufacturing operations in the CLMV subregion. The optimal location for Thai apparel manufacturers was subsequently determined using the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (Fuzzy TOPSIS). The results indicated that Vietnam is the most favorable option. In order to improve the dependability of results, an amended mixture-design scenario analysis was implemented. This analysis assessed the sensitivity and dependability of the proposed model in different scenarios, ensuring its applicability in real-world situations. In contrast to traditional models, this study integrates managerial judgments and preferences into the decision-making procedure, thereby accounting for the complex interdependencies among numerous criteria. The suggested methodology functions as a beneficial instrument for decision-makers, both domestic and international, as it integrates effortlessly into the organizational structure of the CLMV region. By harmonizing objectives pertaining to data acquisition, manipulation, retention, and dissemination, this framework not only enables enhanced decision-making processes, but also optimizes system efficiency. Full article

In light of the rapid rate of change and unforeseen occurrences seen in the realms of technology, market dynamics, and the wider business landscape, there is a growing need for the inclusion of uncertainty and risk factors in the realm of supply chain planning. Supplier evaluation and selection (SES) is a major strategic decision area where the impact of uncertainty and risk can be more proactively dealt with. A review of extant literature reveals that there is a strong need for developing practitioner-oriented and more comprehensive frameworks and models to mitigate both the capability- and performance-related risks, in the context of SES decisions. This paper presents an integrated model to support SES decisions involving quantity discounts and multiple planning periods under stochastic conditions. The proposed model employs the Fuzzy Analytical Hierarchy Process (FAHP), Fuzzy Evaluation Based on Distance from Average Solution EDAS (EDAS-F), and fuzzy stochastic goal programming (FSGP) to effectively address the above requirements. A case study from a garment manufacturing industry is used to demonstrate the efficacy of the proposed model. The findings of the study provide confirmation that the suggested FSIM has the ability to provide substantial advantages in the context of making choices related to quantity discounts in SES. The proposed FSIM model incorporates the use of FAHP and EDAS-F techniques to effectively reduce the number of suppliers to a manageable level, taking into consideration capability-based risks. Additionally, fuzzy stochastic goal programming (FSGP) is employed to mitigate performance-based risks, enabling the selection of suppliers and the allocation of orders among them. The paper contributes to the literature by proposing a comprehensive framework to solve the SES problem, considering certain practical situations faced by organizations. Full article

This study presents an innovative approach for modernizing the garment industry through the fusion of digital human modeling (DHM), virtual modeling for fit sizing, ergonomic body-size data, and e-library resources. The integration of these elements empowers manufacturers to revolutionize their clothing design and production methods, leading to the delivery of unparalleled fit, comfort, and personalization for a wide range of body shapes and sizes. DHM, known for its precision in representing human bodies virtually and integrating anthropometric data, including ergonomic measurements, enhances the shopping experience by providing valuable insights. Consumers gain access to the knowledge necessary for making tailored clothing choices, thereby enhancing the personalization and satisfaction of their shopping experience. The incorporation of e-library resources takes the garment design approach to a data-driven and customer-centric level. Manufacturers can draw upon a wealth of information regarding body-size diversity, fashion trends, and customer preferences, all sourced from e-libraries. This knowledge supports the creation of a diverse range of sizes and styles, promoting inclusivity and relevance. Beyond improving garment fit, this comprehensive integration streamlines design and production processes by reducing the reliance on physical prototypes. This not only enhances efficiency but also contributes to environmental responsibility, fostering a more sustainable and eco-friendly future for the garment industry and embracing the future of fashion, where technology and data converge to create clothing that authentically fits, resonates with consumers, and aligns with the principles of sustainability. This study developed the mobile application integrating with the information in cloud database in order to present the best-suited garment for the user. Full article

The textile and garment manufacturing process in the textile industry produces a significant amount of waste, including fabric scraps, dyes and chemicals, as well as leftover fibers and yarns, leading to environmental pollution. The issue of fabric and garment waste is a major concern within the industry. This review provides an overview of the prevailing waste challenges in the textile sector while exploring the basics of a circular economy. The review incorporates additional findings and relevant research related to these proposals, aiming to promote sustainable solutions for waste reduction in the textile industry. Full article

The worldwide textile sector is one of the most polluting and consuming natural resource value chains. In recent years, trends have demonstrated a linear model driven by fast fashion, increasing the sustainability problems of this sector. The European market and industry are changing the paradigm and promoting some actions towards a sustainable value chain. This paper applies a systematic approach to reviewing scientific research, where Life Cycle Assessment (LCA) is implemented as a tool to understand the impacts considering a holistic life cycle framework, from raw materials to the end-of-life of textile products. The methodology and criteria applied resulted in 73 articles used for qualitative analysis, of which 39 met the criteria for quantitative analysis. The quantitative results reported in the studies were organized and presented by phase of the garment production life cycle (production of fiber, yarn, fabric, manufacturing, and recovery/end of life). From a cradle-to-gate perspective, wool yarn production, by worsted processing, was the material with the highest values (95.70 kg CO₂ eq/kg) for climate change/global warming potential, closely followed by silk fabric (80.90 kg CO₂ eq/kg). Extending to a cradle-to-grave boundary, polyester had the highest values for the previously mentioned category, reaching a potential release of 40.28 kg CO₂ eq per kilogram of polyester textile. When data was available, the user phase predominantly contributed to climate change/global warming potential. Additionally, there were significant differences in maximum and minimum values for some of the materials, which were related to methodological considerations, database inventory, and frequency of use and care considered by the different authors. The study also addresses the considerations and limitations of diverse LCA impact assessment tools. Full article

While nonwoven fabrics have existed for several decades, their usage in personal protective equipment (PPE) has been met with a rapid surge of demands, in part due to the recent COVID-19 pandemic. This review aims to critically examine the current state of nonwoven PPE fabrics by exploring (i) the material constituents and processing steps to produce fibers and bond them, and (ii) how each fabric layer is integrated into a textile, and how the assembled textiles are used as PPE. Firstly, filament fibers are manufactured via dry, wet, and polymer-laid fiber spinning methods. Then the fibers are bonded via chemical, thermal, and mechanical means. Emergent nonwoven processes such as electrospinning and centrifugal spinning to produce unique ultrafine nanofibers are discussed. Nonwoven PPE applications are categorized as filters, medical usage, and protective garments. The role of each nonwoven layer, its role, and textile integration are discussed. Finally, the challenges stemming from the single-use nature of nonwoven PPEs are discussed, especially in the context of growing concerns over sustainability. Then, emerging solutions to address sustainability issues with material and processing innovations are explored. Full article

Near-infrared (NIR) spectroscopy is a widely used technique for determining the composition of textile fibers. This paper analyzes the possibility of using low-cost portable NIR sensors based on InGaAs PIN photodiode array detectors to acquire the NIR spectra of textile samples. The NIR spectra are then processed by applying a sequential application of multivariate statistical methods (principal component analysis, canonical variate analysis, and the k-nearest neighbor classifier) to classify the textile samples based on their composition. This paper tries to solve a real problem faced by a knitwear manufacturer, which arose because different pieces of the same garment were made with “identical” acrylic yarns from two suppliers. The sweaters had a composition of 50% acrylic, 45% wool, and 5% viscose. The problem occurred after the garments were dyed, where different shades were observed due to the different origins of the acrylic yarns. This is a challenging real-world problem for two reasons. First, there is the need to differentiate between acrylic yarns of different origins, which experts say cannot be visually distinguished before garments are dyed. Second, measurements are made in the field using portable NIR sensors rather than in a controlled laboratory using sophisticated and expensive benchtop NIR spectrometers. The experimental results obtained with the portable sensors achieved a classification accuracy of 95%, slightly lower than the 100% obtained with the high-performance laboratory benchtop NIR spectrometer. The results presented in this paper show that portable NIR sensors combined with appropriate multivariate statistical classification methods can be effectively used for on-site textile quality control. Full article

Medical protective clothing should be flexible to ensure free movement of healthcare personnel. This study aimed to investigate the effects of a polymer’s physical properties on the particle composition of a shielding material, constituent component miscibility, and shielding performance. To ensure flexibility by reducing the thickness of the shielding garment, polymer-based composite materials are mainly used as shielding materials. The shielding performance varies depending on whether the polymer used is in an emulsion or powder state. In this study, we found that a shielding film manufactured through an injection process after mixing a polymer in a powder form with tungsten powder exhibited 0.95%–2.5% higher shielding performance than that manufactured using the calendering process with an emulsion polymer. The shell structure formed when using the powder polymer maintains the spacing between the particles owing to the double coating of the tungsten particles and improves their dispersion. Additionally, the primary issue when combining an emulsion polymer and shielding material, that is the aggregation between the shielding material particles and between the polymer particles, could be alleviated, resulting in improved shielding performance. We concluded that the polymer-powder mixing method contributes to the reproducibility of the process technology when manufacturing shielding films. Full article