This paper thoroughly reviews the current state of digital simulation technology and its strategic implementation across applications, primarily focusing on advanced compression garments. Despite the significant impact of three-dimensional digital garment simulators (3DGS) on the apparel and textile industry, their usage has largely been confined to visual prototyping, visual quality check, or marketing tools. Notably, these simulators’ physical or mechanical representation has been understated in the context of advanced functional manufacturing. This review delves into the potential strategic integration of virtual physical properties to augment garment functionalities, particularly within wearables and medical-grade compression fields. The initial phase of this study provides a comprehensive overview of the status of 3D garment simulation tools and their digitisation capabilities. Subsequently, a gap analysis focuses on minimising disparities between simulated and actual physical property assessments. Despite the absence of reliability and standardised testing within a virtual environment, this paper focuses on the relevant literature to gain crucial insights for apparel and textile engineers, providing a nuanced understanding of the capabilities and limitations of 3DGS mechanical representation in enhancing advanced functionalities, specifically customised for diverse end-users.

This paper extracts 13 success factors based on the TOE framework in the three dimensions of Technology, Organization, and Environment (TOE). The factors are developed from investigating the challenges in the digital transformation of textile and garment enterprises and based on the literature and case studies on the success factors of digital transformation within the TOE theoretical framework. Descriptive statistics and factor analysis are performed on ample data from 201 textile and garment enterprises to verify the applicability of the TOE framework for the classification of success factors of digital transformation of textile and garment enterprises. The basic situation of the digital application of textile and garment enterprises is then summarised. The study finds that the organisational factors have the highest scores, followed by technical factors. From the observation indicators of 13 detailed success factors, the average score is greater than 4, indicating that the role of these success factors in textile and garment enterprises is generally recognised. The “digital strategic thinking” of senior managers has the highest score, followed by the “digital transformation project team.” Environmental factor scores of enterprises in the Beijing Tianjin Hebei region are the highest, followed by enterprises in the Yangtze River Delta and Pearl River Delta regions. Medium and large enterprises have higher scores for technical factors and organisational factors. Finally, the paper discusses which success factors should be addressed and improved.

To investigate the aesthetic preferences of consumers towards various sustainable colors, this study aims to assist designers in gaining a comprehensive understanding of consumers’ color preferences during the development of eco-friendly clothing designs. The study begins by establishing a sustainable color matching scheme for clothing and employs the semantic difference method to select perceptual word pairs. Subsequently, a questionnaire survey is conducted to understand consumers’ perceptual evaluation of sustainable colors in clothing. The study further analyzes and ranks the main factors by quantifying the perceptual evaluation and employing the grey correlation degree method. The results indicate that temperament factor, personality factor, and coordination factor are the primary perceptual factors influencing sustainable color. Among these factors, temperament exhibits the strongest correlation with the degree of liking, followed by personality and coordination. When selecting colors, designers should prioritize low brightness and low purity colors. Additionally, blue-green colors are more favored by consumers. The research findings hold significant implications for guiding designers in enhancing the quality and standard of green clothing design while meeting consumers’ perceptual cognitive requirements.

The traditional apparel industry faces challenges to the quarantine of the global COVID-19 pandemic dramatically. The AI technics provide promising solutions for the apparel industry shift from labour-intensive to technic-intensive for survival. However, there are many open problems on how AI could find its application in mass customization. This paper presents practicable methods, frameworks and the curial technologies of AI-promoted apparel mass customization. The AI cloud will apply in traditional knowledge management of customers (KM) with which AI cloud has been trained and make predication of trends and customer’s preferences and enable personalized AI recommendations. With AI measurement flexible digital research development techniques can automatically generate personalized patterns and virtual garment prototypes based on different body shapes. By using the RFID label, the AI cloud could easily provide quality control, products tracing back in the production process and AI logistics. Those solutions and key technologies will benefit the process of apparel industry 4.0.

Text-to-image technology is a technology for mapping target image sets through natural language and is the latest production method for new content. The repousse craft is ancient Chinese gold and silver fine art crafts. Although the craft has been studied, its exploration in digital research is relatively new. To modernise the repouss´e craft, this paper takes the combination of 3D generated drawings of repouss´e craft motifs with text-to-image technology as a research object, applies current artificial intelligence to the study and analyses the possibilities of the combined application and related text specification recommendations, tests and analyses the impact of the changes in the prompt and weighted value settings on the repousse´ craft jewelry design style. The results of the study show that the way the prompt and matting image weights are set plays a key role in the stabilisation of the imaging style. This study not only fills the gap in the combination of repouss´e technology and AI technology but also plays a positive role in the stability of the style of the enhanced text to imaging, which provides a specific parameter basis and a new way of thinking for the future application of AI technology in the design of fashion jewelry and even in the wider field of fashion design.

As a close-fitting clothing for women, bras are in direct contact with women’s breasts and fully fit. The bra structure design based on the difference between upper and lower busts cannot meet individual differences. To solve the problem that traditional large-scale bra production methods cannot meet the individual needs of consumers For this problem, a parametric design method for one-person-one-version personalized bra samples is proposed. By analyzing the morphological characteristics of different breast shapes and the composition factors of bra samples, the breast is regarded as a combined model of ellipsoid and cone. The geometric model of breast shape is established, and the model is analyzed by surface flattening technology, and then the breast is obtained. Mathematical representation of breast characteristic structure lines include root circumference, surface arc length, and lower teat cup arc. According to the relationship between the breast and the size of the bra sample, the parametric relationship model of the bra sample is obtained, and the knowledge model of the bra sample is constructed based on the relationship model, which provides a method for realizing the personalization of the bra sample.

To address the challenges faced by wheelchair users living alone when it comes to wearing trousers, this paper aims to enhance the design of existing trousers by focusing on adaptive structure design and wearing convenience. It also proposes a design concept for wheelchair trouser integration. For adaptive structure design, the structure of the trousers is adapted to the corresponding parts of the wheelchair to obtain an enhanced trouser pattern. Through clo3d virtual fitting verification, the pressure distribution effect of trousers in a sitting posture improved. The connection between the back of the pants and the wheelchair seat is designed to achieve optimal stabilisation. The U-shaped opening design of the wheelchair seat allows for proper storage of the front of the pants, enabling quick circulation and enhancing the independence of wheelchair users. A wear trial experiment was conducted to evaluate the convenience of the prototype trousers. This involved calculating the wearing time and independent coefficient, which provided evidence that the proposed integrated wheelchair trouser design significantly improves wearing convenience.