On May 7, 2026, an industry conference in Keqiao, Zhejiang, signaled a critical shift: textile digitalization is moving from fragmented pilot tests to systemic overhaul. The conference, themed 'Smart Connect Textile City, Digital Create Future,' placed three tracks—digital transformation of dyeing plants, AI-based fabric inspection, and full-process enterprise digitalization—side by side. This juxtaposition itself hints at a change in logic: digitalization is no longer just a departmental tool but a foundational architecture spanning the entire chain of spinning, weaving, dyeing, inspection, and trade.
From Cost Center to Order Creation Center
The most impactful statement came from Long Fangsheng, GM of Zhejiang Meixinda Textile Printing & Dyeing Technology Co., who declared, 'Smart factories are not cost centers but order creation centers.' Meixinda's three-phase evolution of 'shaping, soul-casting, and intelligence-enabling' demonstrates that dyeing enterprises can create incremental value and build competitive barriers if they move beyond mere fabric production. This suggests that the ROI of digital investment is shifting from 'saving money' to 'making money,' a new dimension for buyers and traders when evaluating suppliers.
Meanwhile, Hangzhou Huanyu Shuzhi Technology introduced the TDSD® low-carbon digital dyeing process, achieving nearly 99% water savings, 33% carbon reduction, and 21% chemical reduction. As the EU's Carbon Border Adjustment Mechanism (CBAM) takes shape, this 'spray-and-dye' flexible production model directly impacts export enterprises' green compliance thresholds.
AI Fabric Inspection: From Lab to Plant Floor, but with a Last-Mile Gap
AI fabric inspection was another focal point. Shanghai Kaiqian Intelligent Technology showcased a 'teachable' self-learning AI system that integrates with enterprise production management systems to boost detection efficiency and defect recognition. Nantong Julian Digital Technology developed an AI inspection solution covering online defect warning, warp-weft density monitoring, and production anomaly detection based on real factory needs.
However, the industry consensus is that AI inspection remains in a 'pilot and adaptation phase.' Luo Yucheng, Deputy GM of Keqiao Weaving and Dyeing Industry Brain, identified three bottlenecks:
- Algorithm adaptation difficulties for complex fabrics
- System instability in complex plant environments
- High deployment costs for SMEs
In response, Yan Yan, Vice President of CNTAC, proposed a dual-track strategy: building a shared-knowledge 'textile smart large model' while focusing on vertical-scenario small models. This approach could lower the technical threshold for SMEs.
Supply Chain Collaboration: Data Silos as the Biggest Pain Point
The conference repeatedly highlighted 'data silos.' Hu Song, Director of CNTAC's Information Center, noted five trends: more specific policy guidance, AI applications closer to business processes, intelligent agents as workflow assistants, more digitized green compliance, and more urgent supply chain collaboration. He emphasized that SMEs need low-cost, fast-result digital paths, while large enterprises should shift from system building to data ecosystem leadership.
This 'big-fish-leads-small-fish' approach is already being implemented in Keqiao, which has built a '1+4+N' comprehensive intelligent agent system to digitize and platformize market transactions, information release, trend analysis, and supply chain services. Its 'livestreaming + platform + cross-border e-commerce + overseas warehouse' model is opening up the digital trade chain.