When an AI vision system in a dyeing workshop can identify a broken warp thread in 0.1 seconds, and when water consumption in dyeing processes plummets to just 1% of traditional methods, these are no longer lab demos—they are real-world cases unveiled at the 2026 Textile Digitalization Conference in Keqiao on May 7. The industry has moved from debating 'whether to digitize' to executing 'how to make it work, how to measure ROI, and how to scale.'
Event Context
The conference, themed 'Smart Connect Textile Capital, Digital Create Future—Building New Quality Productivity for the Textile Industry,' was attended by Yan Yan, Vice Chairman of the International Textile Manufacturers Federation and Vice President of the China National Textile and Apparel Council, and Sun Weigang, Deputy Secretary of the China Textile City Party Working Committee. The agenda focused on three core tracks: intelligent transformation of dyeing enterprises, AI-powered fabric inspection, and full-process digital upgrading.
Yan Yan outlined three directions: deepening AI deployment by building a 'textile intelligent large model' and vertical small models; enhancing cross-chain collaboration by breaking data silos; and integrating green manufacturing with a full-industry-chain carbon footprint tracking model. This signals a shift from macro advocacy to concrete technical roadmaps.
Sun Weigang introduced Keqiao's '1+4+N' comprehensive intelligent system and a digital trade chain encompassing 'live streaming + platforms + cross-border e-commerce + overseas warehouses.' Keqiao is transforming from a single market trading hub into a digitally driven industrial nexus.
Industry Impact
The most striking data point came from Hangzhou Huanyu Digital Smart Technology's TDSD® low-carbon digital dyeing process: nearly 99% water savings, 33% carbon reduction, and 21% fewer chemicals. The technology uses self-developed inkjet equipment, new ink materials, and an AI color management system for a 'print-and-dye' production mode. For dyeing enterprises, this means a tangible lowering of the green compliance threshold—environmental regulation becomes a competitive advantage rather than a cost burden.
In the AI fabric inspection arena, Shanghai Kaiqian Intelligent Technology and Nantong Julian Digital showcased 'teachable' self-learning AI systems and multi-scenario solutions covering online defect alerts and warp/weft density monitoring. Traditional manual inspection suffers from recruitment difficulties, fatigue-induced missed defects, and delayed problem detection. AI inspection is moving from pilot adaptation to large-scale deployment. However, Luo Yucheng, Deputy GM of Shaoxing Keqiao Weaving & Dyeing Industrial Brain Operations, cautioned that challenges remain: algorithm adaptation for complex fabrics, system instability in harsh environments, and high implementation costs for SMEs.
Hu Song, Director of the China Textile Information Center, proposed a five-step digitalization method: diagnose current status, select scenarios, fill data gaps, run pilots, and expand capabilities. He emphasized that SMEs should adopt low-cost, fast-result paths, while large enterprises should shift from system building to data ecosystem development. This directly addresses the industry's long-standing confusion: digitalization is not exclusive to big players; small firms can also find entry points.
Long Fangsheng, GM of Zhejiang Meixinda Textile Printing & Dyeing Technology, offered another perspective: smart factories should not be seen as cost centers but as order creation centers. Meixinda's three-phase evolution—'shaping the body, casting the soul, and awakening wisdom'—proves that digital investment can directly translate into market competitiveness.