A Personalized Clothing Design System Enabled by Digital Textile Manufacturing

Chaojiang Hu

Article
2026 / Volume 9 / Pages 120-135
Received 14 August 2025; Accepted 9 September 2025; Published 22 January 2026
https://doi.org/10.31881/TLR.2026.120

Abstract
The global textile industry is transitioning towards sustainable development, necessitating innovations in manufacturing that minimize material waste and enhance efficiency. This paper proposes a computational framework for personalized textile products enabled by digital textile manufacturing (DTM), directly addressing the inefficiencies of traditional textile processing. The system digitizes the entire manufacturing workflow, from raw-material selection to the finished product. It is designed to process a variety of yarn types, including natural fibers such as wool and cotton, as well as synthetic fibers. The architecture integrates modules for versatile user data input, parametric modeling based on materials science principles, and realistic simulation of textile properties. A key innovation is the proposed computational translation architecture, which utilizes a machine-agnostic intermediate representation (IR) to bridge the gap between digital design and production. By operating within a defined parametric design space, the system enables the deterministic and automated generation of machine-specific code for industrial knitting machinery. This approach is designed to drastically reduce material waste associated with cutting. The framework is conceptualized to be extensible, envisioning future integration with downstream digital processes, such as targeted chemical treatments. A validation study demonstrates the fidelity of the proposed logic in producing custom wool garments, confirming the system’s ability to generate deterministic manufacturing data.

Keywords
digital textile manufacturing, textile industry, sustainable manufacturing, natural fibers, yarns