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The aim of this paper is to achieve a reasonable microclimate between clothing and the human body and optimize the custom dress pattern.

An interactive design method of 3D modeling, virtual try-on and heat transfer simulation are used. First, a 3D dress is designed with nonuniform rational B-splines curves and tried on virtually. After that, the heat transfer in the body-air-clothing microclimate and temperature distributions on the clothing surface are obtained. Based on the heat transfer in the body-air-clothing system, we design a method to improve the thermal comfort by optimizing the garment pattern digitally. Then, this paper utilized two heat transfer validating indexes to quantify the improvement of thermal comfort, and evaluate the modified model of dress.

The microclimate under the clothing is varied with the air gap distance, and the heat transfer on the area of the clavicle, bust point and front abandon are higher than other parts due to the narrow air gaps. In view of thermal comfort, the pattern optimization changes the distance ease and reforms the air circulating efficiency. The mean heat transfer and its standard variance are changing by about 10% and more than 20%. Thus, the heat transfer evaluation indexes are suitable to represent the heat transfer and thermal comfort in the microclimate system.

It can be concluded that the methodology proposed in this paper has the advantage of interactive design, 3D visualization and local heat transfer simulation. This technology meets the need of personalized customization and well-considered garment and has broad application prospects.

This study demonstrates that modifying the distance ease on body key girths based on heat transfer is a reliable way to improve thermal comfort. This method meets the consumers’ demand of the comfort of body-fit clothing under the condition of daily activities.

• 3D air gap distributions.

• Heat transfer varies with air gap distance.

• Thermal comfort can be improved by optimizing garment pattern.

3D air gap distributions.

Heat transfer varies with air gap distance.

Thermal comfort can be improved by optimizing garment pattern.

The aim of this study is to present an overview of sustainable practices in the development of waterproof breathable fabrics for garments. It aims to provide insights into the current state of academic research in this domain and identify and analyze major sustainable trends in the field.

This study conducts a thorough examination of research publications sourced from the Scopus database spanning the years 2013–2023 by employing a systematic approach. The research utilizes both descriptive analysis and content analysis to identify trends, notable journals and leading countries in sustainable waterproof breathable fabric development.

The study reveals a notable increase in studies focusing on sustainable approaches in the development of waterproof breathable fabrics for garments. Descriptive analysis highlights the most prominent journal and leading country in terms of research volume. Content analysis identifies four key trends: minimizing chemical usage, developing easily degradable materials, creating fabrics promoting health and well-being and initiatives to reduce energy consumption.

The main limitation of this research lies in its exclusive reliance on the Scopus database.

The insights derived from this study offer practical guidance for prospective researchers interested in investigating sustainable approaches to developing waterproof breathable fabric for garments. The identified trends provide a foundation for aligning research endeavors with contemporary global perspectives, facilitating the integration of sustainable methodologies into the garment industry.

This systematic literature review contributes original insights by synthesizing current research trends and outlining evolving sustainable practices in the development of waterproof breathable fabrics. The identification of key focus areas adds a novel perspective to existing knowledge.

Perspiration and heat are produced by the body and must be eliminated to maintain a stable body temperature. Sweat, heat and air must pass through the fabric to be comfortable. The cloth absorbs sweat and then releases it, allowing the body to chill down. By capillary action, moisture is driven away from fabric pores or sucked out of yarns. Convectional air movement improves sweat drainage, which may aid in body temperature reduction. Clothing reduces the skin's ability to transport heat and moisture to the outside. Excessive moisture makes clothing stick to the skin, whereas excessive heat induces heat stress, making the user uncomfortable. Wet heat loss is significantly more difficult to understand than dry heat loss. The purpose of this study is to provided a good compilation of complete information on wet thermal comfort of textile and technological elements to be consider while constructing protective apparel.

This paper aims to critically review studies on the thermal comfort of textiles in wet conditions and assess the results to guide future research.

Several recent studies focused on wet textiles' impact on comfort. Moisture reduces the fabric's thermal insulation value while also altering its moisture characteristics. Moisture and heat conductivity were linked. Sweat and other factors impact fabric comfort. So, while evaluating a fabric's comfort, consider both external and inside moisture.

The systematic literature review in this research focuses on wet thermal comfort and technological elements to consider while constructing protective apparel.

The changing roles of the United Nations (UN) and national institutions have made addressing climate change a critical concern for many multinational enterprises’ (MNEs) survival and growth. This chapter discusses how such institutions, which vary in their nature and characteristics, shape firm strategies for climate change adaptation. Exploring different versions of institutional theory, the chapter demonstrates how and why institutional characteristics affect typical patterns of firm ownership, governance, and capabilities. These, in turn, influence companies’ internationalisation and climate-change strategies. Climate change poses challenges to how we understand firms’ strategic decisions from both an international business (IB) (HQ–subsidiary relations) and global value chains (GVC) (buyer–supplier relations) perspective. However, climate change also provides opportunities for companies to gain competitive advantages – if firms can reconfigure and adapt faster than their competitors. Existing IB and GVC research tends to downplay the importance of climate change strategies and the ways in which coherent or dysfunctional institutions affect firms’ reconfiguration and adaptation strategies in a globally dispersed network of value creation. This chapter presents a perspective on the institutional conditions that affect firms’ climate change strategies regarding ownership, location, and internalisation (OLI), and GVCs, with ‘investment’ and ‘emerging standards’ playing a significant role. The authors illustrate the discussion using several examples from the Global South (i.e. Bangladesh) and the Global North (i.e. Denmark, Sweden, and Germany) with a special emphasis on the garment industry. The aim is to encourage future research to examine how a ‘business systems’, or varieties of capitalism, institutional perspective can complement the analysis of sustainability and climate change strategies in IB and GVC studies.

This study aims to fabricate a multifunctional electromagnetic interference (EMI) shielding composite fabric with simultaneous high-efficiency photothermal conversion and Joule heating performances.

A multifunctional polypyrrole (PPy) hydrogel/multiwalled carbon nanotube (MWCNT)/cotton EMI shielding composite fabric (hereafter denoted as PHMC) was prepared by loading MWCNT onto tannin-treated cotton fabric, followed by in situ crosslinking-polymerization to synthesize three-dimensional (3D) conductive networked PPy hydrogel on the surface of MWCNT-coated cotton fabric.

Benefiting from the unique interconnected 3D networked conductive structure of PPy hydrogel, the obtained PHMC exhibited a high EMI-shielding effectiveness vale of 48 dB (the absorbing electromagnetic wave accounted for 84%) within a large frequency range (8.2–12.4 GHz). Moreover, the temperature of the laminated fabric reached 54°C within 900 s under 15 V, and it required more than 100 s to return to room temperature (28.7°C). When the light intensity was adjusted to 150 mW/cm², the PHMC temperature was about 38.2°C after lighting for 900 s, indicating high-efficiency electro-photothermal effect function.

This paper provides a novel strategy for designing a type of multifunctional EMI shielding composite fabric with great promise for wearable smart garments, EMI shielding and personal heating applications.

In recent years, the demand for garments has significantly increased, requiring manufacturers to speed up their production to attract customers. Cut order planning (COP) is one of the most important processes in the apparel manufacturing industry. The appropriate stencil arrangement can reduce costs and fabric waste. The COP problem focuses on determining the size combination for a pattern, which is determined by the length of the cutting table, width, demand order, and height of the cutting equipment.

This study proposes new heuristics: genetic algorithm (GA), symbiotic organism search, and divide-and-search-based Lite heuristic and a One-by-One (ObO) heuristic to address the COP problem. The objective of the COP problem is to determine the optimal combination of stencils to meet demand requirements and minimize the total fabric length.

A comparison between our proposed heuristics and other simulated annealing and GA-based heuristics, and a hybrid approach (conventional algorithm + GA) was conducted to demonstrate the effectiveness and efficiency of the proposed heuristics. The test results show that the ObO heuristic can significantly improve the solution efficiency and find the near optimal solution for extreme demands.

This paper proposes a new heuristic, the One-by-One (ObO) heuristic, to solve the COP problem. The results show that the proposed approaches overcome the long operation time required to determine the fitting arrangement of stencils. In particular, our proposed ObO heuristic can significantly improve the solution efficiency, i.e. finding the near optimal solution for extreme demands within a very short time.

Virtual try-on (VTO) technology with three-dimensional (3D) body scanning in a mobile application is a relatively new technique for selling custom-fit apparel. VTO involves scanning and measuring one's body and visualizing the fit of a garment on a 3D avatar. The purpose of this study is to explore consumers' experiences toward the custom-fit T-shirts and online mass customization (MC) services using the VTO technology found in online consumer reviews (OCRs).

A total of 297 OCRs were collected from the Amazon's Made for You site that uses VTO technology for the MC process. A qualitative content analysis, within a mixed method research process, was used to determine systematically the meanings within qualitative data with quantitative results. In the qualitative approach, combinations of two coding processes were employed, which were concept-driven (i.e., deductive/a priori) and data-driven (i.e., inductive/emergent) coding processes. In the quantitative approach, the prevalence of each coding in terms of its valence was calculated based on frequencies. Intercoder reliability reached 96 per cent.

In OCRs of customized apparel products and online MC services using VTO technology, consumers described expectations, perceived performance, dis/confirmation, dis/satisfaction, outcomes of dis/satisfaction and descriptive information. Those with expectations often expressed skepticism about the product and the MC process using VTO technology at the pre-consumption stage. In OCRs, they used four product dimensions and two service dimensions of perceived performance. Consumers had positive (negative) confirmation when the performance of the T-shirts and/or services worked better (worse) than their expectations. The OCRs also included dis/satisfaction with a product and/or service, its outcomes and descriptive information.

This study identified a resulting framework to identify the content in OCRs of the custom-fit T-shirts and online MC services that use VTO technology. This study extends the expectation confirmation theory by adding multiple dimensions (i.e., four product dimensions and two service dimensions) as well as more outcomes of dis/satisfaction (not limited to repurchase intentions). This study provides practical suggestions for online MC companies who are using or planning to use VTO technology on how to improve consumers' satisfaction with customized T-shirts using VTO technology.

This paper aims to answer the questions of what clothing practices related to sustainable fashion can be observed in young consumers' daily lives in Finland’s capital region and what prevents their further proliferation.

This is qualitative research that draws from 22 semi-structured interviews with high school students in the capital area of Finland. The data were analyzed with the use of thematic analysis, a flexible method of data analysis that allows for the extraction of categories from both theoretical concepts and data.

This paper contributes to studies of young people’s consumption with the practice theory approach, putting forward the category of following sustainable fashion as an integrative practice. The three-element model of the practice theory allows answering the question of challenges that prevent the practice from shaping. The paper further advances this approach by identifying a list of context-specific dispersed practices incorporated into sustainable fashion.

The study suggests practical ways of improving clothing consumption based on the practice theory approach and findings from empirical research. Sustainable practices require competences, knowledge and skills that the school, as an institution working closely with high school students, could help develop.

The study contributes to the current studies of sustainability and youth culture of consumption with a practice theory approach and findings, related to a particular context of a country from Northern Europe.

Ultrasonic welding is an emerging apparel manufacturing technique. However, the applications are widely explored in the field of technical textiles, with less exploration in the apparel endues. The purpose of this study is to explore the application of ultrasonic welding in apparel by analyzing the impacts of different parameters.

This study analyzed the influence of ultrasonic welding parameters, including pressure, welding speed and ultrasonic power on the seam performances (seam strength, seam bursting strength, seam thickness and seam stiffness). The parameters are optimized using Box–Behnken experimental design to achieve better seam performances.

The properties of ultrasonic seams are influenced by welding and fabric properties. Ultrasonically welded seams showed better performances in the case of comfort properties of seams, whereas the functional properties are lesser compared to conventional seams.

The findings of the research clearly outline the level of influence of different parameters on the performance of the ultrasonically welded seams in knitted fabrics, which can greatly help in applying ultrasonic welding manufacturing methods in apparel manufacturing.

The textile industry holds immense significance in the economy of any nation, particularly in the production of synthetic yarn and fabrics. Consequently, the pursuit of acquiring high-quality products at a reduced cost has become a significant concern for countries. The primary objective of this research is to leverage data mining and data intelligence techniques to enhance and refine the production process of texturized yarn by developing an intelligent operating guide that enables the adjustment of production process parameters in the texturized yarn manufacturing process, based on the specifications of raw materials.

This research undertook a systematic literature review to explore the various factors that influence yarn quality. Data mining techniques, including deep learning, K-nearest neighbor (KNN), decision tree, Naïve Bayes, support vector machine and VOTE, were employed to identify the most crucial factors. Subsequently, an executive and dynamic guide was developed utilizing data intelligence tools such as Power BI (Business Intelligence). The proposed model was then applied to the production process of a textile company in Iran 2020 to 2021.

The results of this research highlight that the production process parameters exert a more significant influence on texturized yarn quality than the characteristics of raw materials. The executive production guide was designed by selecting the optimal combination of production process parameters, namely draw ratio, D/Y and primary temperature, with the incorporation of limiting indexes derived from the raw material characteristics to predict tenacity and elongation.

This paper contributes by introducing a novel method for creating a dynamic guide. An intelligent and dynamic guide for tenacity and elongation in texturized yarn production was proposed, boasting an approximate accuracy rate of 80%. This developed guide is dynamic and seamlessly integrated with the production database. It undergoes regular updates every three months, incorporating the selected features of the process and raw materials, their respective thresholds, and the predicted levels of elongation and tenacity.