This paper examines the digital transformation of the textile and fashion industry, focusing on the alignment with sustainability principles through the integration of Industry 4.0 technologies. The introduction highlights the urgency of transitioning from conventional production methods to innovative, digitally enabled systems that promote a circular economy and resource efficiency. The main research questions address the contribution of Industry 4.0 elements to sustainable solutions, the directions of digitalization within the apparel sector, and the significant impact of digital technologies on the achievement of sustainability goals. The theoretical framework examines sustainability in the textile industry and emphasizes the need for a green transformation facilitated by digital technologies to reduce environmental impacts. Industry 4.0 concepts, as discussed in The Concept of Industry 4.0 in the Textile and Apparel Sector, are revolutionizing production through technologies such as IoT, AI, and blockchain, enabling traceability, customization, and energy-efficient operations. The paper also explores the evolution of the fashion and apparel industry into a high-tech sector, highlighting advances such as CAD-CAM systems, digital printing, and 3D technologies that improve precision, reduce waste, and support sustainable practices. In its conclusion, the paper emphasizes the crucial role of interdisciplinary collaboration, regulatory frameworks, and investment in skills development to overcome the challenges of implementing digital and sustainable practices. It posits that a strategic embrace of digital ecosystems and Industry 4.0 technologies is essential for creating a resilient and sustainable textile industry that is aligned with environmental and societal goals.

Contemporary CAD systems enable 3D clothing simulation for the purpose of predicting the appearance and behavior of conventional and intelligent clothing in real conditions. The physical and mechanical properties of the fabric and the simulation parameters play an important role in this issue. The paper presents an analysis of the parameters of the polygonal computer model that affect fabric drape simulation. Experimental research on physical and mechanical properties were performed for nine fabrics. For this purpose, the values of the parameters for the tensile, bending, shear, and compression properties were determined at low loads, while the complex deformations were analyzed using Cusick drape meter devices. The fabric drape simulations were performed using the 2D/3D CAD system for a computer clothing design on a disk model, corresponding to real testing on the drape tester in order to allow a correlation analysis between the values of drape parameters of the simulated fabrics and the realistically measured values for each fabric. Each fabric was simulated as a polygonal model with a variable related to the side length of the polygon to analyze the influence of the polygon size, i.e., mesh density, on the model behavior in the simulation. Based on the simulated fabric drape shape, the values of the areas within the curves necessary to calculate the drape coefficients of the simulated fabrics were determined in the program for 3D modelling. The results were statistically processed and correlations between the values of the drape coefficients and the optimal parameters for simulating certain physical and mechanical properties of the fabric were determined. The results showed that the mesh density of the polygonal model is an important parameter for the simulation results.

In the context of sustainable fashion, this paper presents research on the impact of property assessment methods of textile materials and pigment digital printing on the mechanical properties of fabrics and their 3D simulation in the development of digital prototypes for clothing design. Six woven fabrics, with and without a textile ink-jet print, were tested using a KES-FB measuring system and digitized using SEDDI Textura AI technology. The determined mechanical parameters were used for 3D draping simulations based on Cusick Drape Meter method, as well as for the simulation of frilly women’s skirt models. The research showed a good correlation between the draping of real fabric samples and their 3D simulations, particularly supporting the use of AI for fabric assessments due to its sustainability. The drape analysis, performed on the digital 3D prototypes of a frilly women’s skirt model in two different lengths, showed the influence of fabric ink-jet printing on the drape properties, which can be explained by some structural parameters and determined changes in mechanical parameters between unprinted and printed fabric samples. The results provide valuable insights for objective evaluation of clothing digital 3D prototypes, which is a very significant element in the production process from a sustainability point of view and is becoming increasingly prominent as a method for developing new clothing designs that is gradually replacing the traditional, less environmentally friendly approach of creating numerous physical test samples.

3D scanning and CAD technology is used in engineering and ergonomics practice for several years, due to their admissibility in producing accurate 3D object representation, scan data restoration and modification. Lately the application was extended for reconstructing and modelling 3D scan data of the human body, since it enables tracing the geometry information and precise measurement analysis. In this study, this technology was applied to analyse the scanned models of dressed human body. The changes in microclimatic air distribution and clothing area due to changing upper limb positions, simulating functional reaching movements for the aircrew personnel, were calculated using 3D scanning and CAD technology. The results have proven the posture representing the overall lateral limit of reach to be the best posture for the volume and area identification by means of the 3D scanning. The study will further serve as basis to modify clothing prototypes for improved thermal protection.

This paper presents research in the field of computer-aided 3D clothing design, focusing on an investigation of three methods for determining the mechanical properties of woven fabrics and their impact on 3D clothing simulations in the context of sustainable apparel development. Five mechanical parameters were analyzed: tensile elongation in the warp and weft directions, shear stiffness, bending stiffness, specific weight, and fabric thickness. These parameters were integrated into the CLO3D CAD software v.2025.0.408, using data obtained via the KES-FB system, the Fabric Kit protocol, and the AI-based tool, SEDDI Textura 2024. Simulations of women’s blouse and trousers were evaluated using dynamic tests and validated by real prototypes measured with the ARAMIS optical 3D system. Results show average differences between digital and real prototype deformation data up to 6% with an 8% standard deviation, confirming the high accuracy of 3D simulations based on the determined mechanical parameters of the real fabric sample. Notably, the AI-based method demonstrated excellent simulation results compared with real garments, highlighting its potential for accessible, sustainable, and scalable fabric digitization. Presented research is entirely in line with the current trends of digitization and sustainability in the textile industry. It contributes to the advancement of efficient digital prototyping workflows and emphasizes the importance of reliable mechanical characterization for predictive garment modeling.

This paper presents a study on the possible application of the Aramis optical 3D measuring system for analysing dynamic deformations of the human body in motion. A methodology for the use of Aramis in the field of dynamic anthropometry is presented for the first time in this study. Five body movements were analysed on three female test subjects. Based on the surface deformation results, a set of ten characteristic body measurements, relevant for garment design and construction, were identified, analysed and compared to reference values obtained using laser 3D body scanning technology. Changes in measurement dimensions during particular movements were determined in relation to initial measurements in a static standing position, where the greatest body measure deformation recorded was a 37% increase in back width during arm-forward movement and a 23% elongation of the posterior lower body length during forward bending. A comparative analysis of the results indicated a high level of precision of measurements obtained using the Aramis system, which achieved mean absolute errors of less than 3 mm and relative errors of less than 3%, thus emphasising the ability to monitor and analyse surface deformations of the body throughout entire movements and not just in final body positions, as is the case with the use of 3D body scanning technology. The proposed measurement methodology from this study offers valuable data for the development of garment model design, material selection and clothing pattern construction according to the requirements of dynamic anthropometry.