AI-driven generation of seamless fabric patterns with automated machine-aware output for textile industrial processes

Artificial Intelligence (AI) and Machine Learning (ML) are increasingly transforming industrial processes through automation, efficiency, and customization. In the textile industry, designing fabric patterns and adapting them to weaving and printing machines remain complex tasks that require substantial expertise. This article proposes an ML-based framework for generating textile patterns and adapting them to machine-specific production constraints. The approach combines historical design data and production specifications to support predictive and generative models capable of creating new patterns while determining corresponding machine settings. By directly linking pattern generation with machine configuration, the framework reduces manual intervention, shortens the design-to-production cycle, and lowers the risk of configuration errors. It also supports mass customization by enabling rapid creation and production of personalized textiles. Overall, the solution advances textile digitalization by integrating AI-driven design automation with intelligent manufacturing processes aligned with the principles of Industry 4.0 and Industry 5.0 within modern smart textile manufacturing environments.