Artificial Intelligence and Digital Technologies in Garment Design, Pattern Development and Apparel Manufacturing
Keywords:
Artificial Intelligence; Digital Fashion; Garment Design; Pattern Development; 3d Virtual Prototyping; Apparel Manufacturing; Machine Learning; Textile TechnologyAbstract
The use of Artificial Intelligence (AI) and digital technologies is transforming the fashion value chain from concept through to pattern making, sampling, manufacturing and selling. The current landscape and future trend of AI's integration into garment design and apparel production is analysed in this article, using evidence from peer-reviewed literature, industry reports, and data from case studies. Six applications areas are explored: Generative AI for design ideation; 3D virtual sampling and digital twins; AI pattern grading and marker optimization; Computer vision for automated cutting and sewing; AI demand forecasting; Machine learning for mass personalization. Combining these published data, digital assisted workflows may be able to shorten design-to-sample times by as much as 65-75% and pattern-grading times by about 60% while AI based forecasting models are reported to be able to decrease the demand-forecasting error by 20-50% compared to traditional statistical models. The market for AI application in fashion is expected to have grown by over five times in the last five years (2018–2023) and is projected to expand at a compound annual growth rate of 57% through 2028.The global market for AI applications in fashion grew by more than five times in the last five years (2018–2023) and is expected to experience compound annual growth rate of 57% through 2028. Nevertheless, the study outlines ongoing challenges, such as cost of implementation, data-quality and interoperability issues, workforce reskilling, and unanswered questions of authorship of design and algorithmic bias. The article ends with a proposed structure for the responsible introduction of AI into the apparel value chain and a list of directions for future research, such as “explainable” AI in the support of design decisions, and “standardized” digital-twin interoperability protocols.


