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This study aims to increase the novelty of clothing design and fabric texture. The element library that can be used for design is systematically summarized. The element database can also be continuously filled according to the existing logic to realize the diversity of design. Improve the theory of fashion design, expand the designer's design ideas and improve design efficiency. Clear design steps and logic can help students and machines learn the design process and promote the development of intelligent design. And verify the feasibility of the simulation software to assist pleated clothing design.

Firstly, according to the logical framework of origami theory, different innovative designs and combined designs are made for the basic units of hyperbolic paraboloid, and the element library that can be used for design is systematically summarized. This database can also be continuously filled according to the existing logic to realize the diversity of design. Secondly, it summarizes three methods of pleated element filling clothing – uniform filling method, the irregular filling method and geometric addition method – that improve the theory of fashion design, expand the designer's design ideas and improve design efficiency. Clear design steps and logic can help students and machines learn the design process and promote the development of intelligent design. Finally, the virtual software is used to simulate the effect of pleated clothing, and the three-dimensional simulation software 3dclo is used to make an empirical study on the application of hyperbolic paraboloid origami in clothing pleated design to verify the feasibility of the simulation software to assist pleated clothing design.

The theoretical results of hyperbolic paraboloid origami are collected and arranged to establish the element library of hyperbolic paraboloid origami. The results expand the designer's design ideas and auxiliary design technology and improve the design efficiency using a sample of hyperbolic paraboloid fabric to verify its practicability and three-dimensional clothing simulation software for exploring the design. The design rules of hyperbolic paraboloid clothing and the realization method of fabric are summarized, including the expansion and combing of elements, the application of size and shape and the method of combination.

Owing to the hyperbolic paraboloid origami’s length shrinkage, the loose computation of clothing requires targeted computation. This paper solely applies a paper model for estimating the shrinkage, and then we tend to subsequently explore the way to precisely compute the porosity, to determine the existing differences in the two-dimensional shrinkage of hyperbolic paraboloid creases of varying materials and to know if the clothing after large-scale production is capable of reaching the anticipated value.

The exploration of this experiment brings a new 3D experiment process to the design process.

This experiment brings new possibilities for the development of virtual fitting and virtual display in the industry.

This study combines hyperbolic paraboloid origami and clothing and combs and expands the unit with logical thinking to expand the designer's design ideas.

Accurate and automatic clothing pattern making is very important in personalized clothing customization and virtual fitting room applications. Clothing pattern generating as well as virtual clothing simulation is an attractive research issue both in clothing industry and computer graphics.

Physics-based method is an effective way to model dynamic process and generate realistic clothing animation. Due to conceptual simplicity and computational speed, mass-spring model is frequently used to simulate deformable and soft objects follow the natural physical rules. We present a physics-based clothing pattern generating framework by using scanned human body model. After giving a scanned human body model, first, we extract feature points, planes and curves on the 3D model by geometric analysis, and then, we construct a remeshed surface which has been formatted to connected quad meshes. Second, for each clothing piece in 3D, we construct a mass-spring model with same topological structures, and conduct a typical time integration algorithm to the mass-spring model. Finally, we get the convergent clothing pieces in 2D of all clothing parts, and we reconnected parts which are adjacent on 3D model to generate the basic clothing pattern.

The results show that the presented method is a feasible way for clothing pattern generating by use of scanned human body model.

The main contribution of this work is twofold: one is the geometric algorithm to scanned human body model, which is specially conducted for clothing pattern design to extract feature points, planes and curves. This is the crucial base for suit clothing pattern generating. Another is the physics-based pattern generating algorithm which flattens the 3D shape to 2D shape of cloth pattern pieces.

This paper aims to examine and compare the export performance and competitiveness of Indian and Chinese textile and clothing industry in post-multifibre arrangement (MFA) era.

Balassa’s revealed comparative advantage Index is used to assess the competitiveness of Indian and Chinese textile and clothing exports.

The results indicate that China’s textiles and garments sector holds a greater proportion of the global market compared with India. India has a robust comparative advantage in silk, carpets and cotton post-MFA. Vegetable textile fibers, paper yarn and woven fabrics of paper yarn are also competitive. China had a strong comparative advantage in silk and fabrics; special woven fabrics, tafted textile fabrics, lace, tapestries, trimmings and embroidery in 2005. China also recorded comparative advantage in silk, man-made filaments: strip and the like of man-made textile materials, fabrics; special woven fabrics, tafted textile fabrics, lace, tapestries, trimmings and embroidery and fabrics; knitted or crocheted in 2021.

This study’s results and recommendations could assist the Indian and Chinese Governments develop policies to upgrade their garment industries.

Though vast literature reviews are available for textile and apparel export performance in India and China separately, there are few studies on comparisons. This study is a significant attempt to evaluate India and China’s competitiveness in the global market.

The case is written on the basis of published sources only.

Doodlage, a start-up incorporated in 2012 by Kriti Tula, Paras Arora and Vaibhav Kapoor, used discarded waste to create sustainable fashion products. It had a first-mover advantage in recycled fashion goods in the first 10 years of its existence. The company contributed to sustainable fashion by providing an alternative to fast fashion production, creating enormous clothing waste and environmental degradation. In the first quarter of 2022, it saved and reused 15,000 m of fabric waste. From 2018 to 2021, the company grew 150% annually, targeting the right customers and regions to expand its business. It ensured that postproduction industrial waste and postconsumption garments were used to produce clothes. It also confirmed that the waste generated in its fabric screening process was used to create stationery items and other valuable accessories.

However, the sustainable fashion model that gave the company a competitive advantage became obsolete in 2022 due to increasing competition in the industry as various players using unique ideas entered the market. The company is encountering operational and logistical challenges that are affecting its performance. The demand for its products was also subdued due to high prices of upcycled and recycled clothes and less consumer spending post-COVID pandemic. The competitors of Doodlage offered multiple products produced using environmentally friendly farming and manufacturing techniques, attracting sustainable purchasers. What should be the new portfolio of products for the company to explore future growth opportunities? Considering their vast price, can consumers be encouraged to buy upcycled clothes? How should the company ride the winds of change in the industry?

The instructor should initiate the class discussion by asking questions such as how frequently do you shop for clothes? Do you care about the fabric of your apparel? After you discard your clothes, do you think about where these goods finally end up? Data on the amount of total waste generated in the fashion industry should be communicated to students to connect it with the importance of the concept of circular economy. Post this, the instructor should introduce the business model of Doodlage to bring the discussion into the context of the fashion industry before going ahead to discuss the company’s dilemma.

The apparel and textile sector poses a significant environmental challenge due to its substantial contribution to pollution in the form of air, water and soil pollution. To combat these issues, the adoption of sustainable practices is essential. This study aims to identify and analyse the barriers that hinder the progress of sustainability in the apparel and textile industry. By consulting experts in the field, critical barriers were identified and given special attention.

To achieve the research objective, an integrated approach involving Interpretive Structural Modelling (ISM) and fuzzy MICMAC decision-making techniques was employed. The results were further validated through the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method.

The findings highlight that barrier related to clothing disposal, inadequate adaptation to modern technology, challenges affecting sector efficiency and issues related to fashion design are crucial in influencing the remaining six barriers. Based on the outcomes of the DEMATEL method, a comprehensive cause-and-effect diagram was constructed to gain a deeper understanding of these challenges.

This research provides valuable insights for policymakers and stakeholders in the apparel and textile industry. It offers a strategic framework to address and overcome sustainability barriers, promoting the development of a more environmentally responsible and resilient sector.

The purpose of this research is to conduct an in-depth investigation of the barriers apparel and textile sectors. It is feasible that both the management team and the medical experts who provide direct patient care could benefit from this research.

The objective of this study was to develop wearable suit platforms with various anchoring structure designs with the intention of improving wearability and enhancing user satisfaction.

This study selected fabrics and materials for the suit platform through material performance tests. Two anchoring structure designs, 11-type and X-type are compared with regular clothing under control conditions. To evaluate the comfort level of the wearable suit platform, a satisfaction survey and electroencephalogram (EEG) measurements are conducted to triangulate the findings.

The 11-type exhibited higher values in comfort indicators such as α, θ, α/High-β and lower values in concentration or stress indicators such as β, ϒ, sensorimotor rhythm (SMR)+Mid-β/θ, and a spectral edge frequency of 95% compared to the X-type while walking. The 11-type offers greater comfort and satisfaction compared to the X-type when lifting based on the EEG measurements and the participants survey.

It is recommended to implement the 11-type when designing wearable suit platforms. These findings offer essential data on wearability, which can guide the development of soft wearable robots.

Based on the knowledge-attitude-behavior model, this study is aimed at investigating the influential mechanism underlying the purchase of green clothing by dividing this clothing category into green home-in wear and home-out wear within the context of green consumption. The mediating effects of perceived greenwashing (PG), perceived value (PV) and expected moral benefit (EMB) and the moderating effect of green clothing type (GCT) were examined.

The data for this study were collected from 366 valid samples through a between-subject design survey administered in China. Moderation analysis and mediation analysis using SPSS/PROCESS macro were applied to test the proposed hypotheses.

The results indicate that consumers' level of environmental knowledge (EKL) not only has a direct effect on purchase intention (PI) but also has an indirect effect through perceived value and expected moral benefit. However, perceived greenwashing did not play a mediating role in this relationship.

The study's findings show a moderating effect of green clothing type (green home-in wear vs green home-out wear). That is, compared to green home-out wear, the relationship between expected moral benefit and perceived greenwashing for green home-in wear had a weaker negative effect on purchase intentions.

This paper reviews the pros and cons of different parametric modeling methods, which can provide a theoretical reference for parametric reconstruction of 3D human body models for virtual fitting.

In this study, we briefly analyze the mainstream datasets of models of the human body used in the area to provide a foundation for parametric methods of such reconstruction. We then analyze and compare parametric methods of reconstruction based on their use of the following forms of input data: point cloud data, image contours, sizes of features and points representing the joints. Finally, we summarize the advantages and problems of each method as well as the current challenges to the use of parametric modeling in virtual fitting and the opportunities provided by it.

Considering the aspects of integrity and accurate of representations of the shape and posture of the body, and the efficiency of the calculation of the requisite parameters, the reconstruction method of human body by integrating orthogonal image contour morphological features, multifeature size constraints and joint point positioning can better represent human body shape, posture and personalized feature size and has higher research value.

This article obtains a research thinking for reconstructing a 3D model for virtual fitting that is based on three kinds of data, which is helpful for establishing personalized and high-precision human body models.

This study aims to investigate the ecological awareness of Chinese consumers towards fast fashion and examine the effect of social sustainability claims on green brand image and purchase intentions in China, considering China’s unique environmental policy landscape and its significant role in the global fast fashion industry. The study explores the role of altruistic values in promoting sustainability within the well-known fast fashion brand “H” and how they shape brand image, consumer satisfaction and brand equity.

The study collected data from 257 Chinese participants and used a serial mediation model through the PROCESS macro in SPSS to analyse the correlation between green brand image, created through sustainability claims and consumer purchase intentions. The model also assessed the intermediary effects of brand image, satisfaction and equity.

The findings of the research indicate a direct and positive relationship between green brand image and consumer purchase intentions, emphasising the need for clothing and textile industry marketers to strategically promote altruistic values in their sustainability efforts and highlighting the importance of ecological awareness in shaping consumer behaviour in the Chinese context. This approach enhances green satisfaction and green brand equity and ultimately leads to higher green purchase intentions.

This study provides significant insights into the effectiveness of incorporating social sustainability claims in advertising to improve a brand’s green image and influence consumer behaviour. It emphasises the importance of altruistic values in sustainability strategies, offering valuable guidelines for marketers in enhancing green satisfaction and brand equity, thereby boosting consumer purchase intentions in the context of green branding and sustainability advertising. Focussing specifically on the Chinese market, this research sheds light on the impact of ecological awareness among Chinese consumers within the fast-fashion industry. Given China’s substantial role in shaping global fast-fashion production and its evolving environmental policies, this focus adds significant depth to our understanding of sustainability claims’ influence within this crucial consumer base.

This study aims to quantify and prioritize the main causes of lean wastes and to apply reduction methods by employing better waste cause identification methodologies.

We employed fuzzy techniques for order preference by similarity to the ideal solution (FTOPSIS), fuzzy analytical hierarchy process (FAHP), and failure mode effect analysis (FMEA) to determine the causes of defects. To determine the current defect cause identification procedures, time studies, checklists, and process flow charts were employed. The study focuses on the sewing department of a clothing industry in Addis Ababa, Ethiopia.

These techniques outperform conventional techniques and offer a better solution for challenging decision-making situations. Each lean waste’s FMEA criteria, such as severity, occurrence, and detectability, were examined. A pairwise comparison revealed that defect has a larger effect than other lean wastes. Defects were mostly caused by inadequate operator training. To minimize lean waste, prioritizing their causes is crucial.

The research focuses on a case company and the result could not be generalized for the whole industry.

The study used quantitative approaches to quantify and prioritize the causes of lean waste in the garment industry and provides insight for industrialists to focus on the waste causes to improve their quality performance.

The methodology of integrating FMEA with FAHP and FTOPSIS was the new contribution to have a better solution to decision variables by considering the severity, occurrence, and detectability of the causes of wastes. The data collection approach was based on experts’ focus group discussion to rate the main causes of defects which could provide optimal values of defect cause prioritization.