A textile industry conference in Keqiao is shifting the conversation from 'whether to digitalize' to 'how and how deeply.' Held on May 7, the 2026 Textile Digitalization Conference sent a clear signal: digitalization is no longer a nice-to-have concept but a core capability determining a company's survival in the next five years.
Yan Yan, Vice President of the China National Textile and Apparel Council, outlined three directional judgments: AI is accelerating from concept validation to large-scale deployment; full-chain collaboration must break data silos; and green manufacturing needs traceable carbon footprint models. These three points directly address the industry's most painful bottlenecks: production efficiency, cross-link data isolation, and export market green compliance pressures.
Three Tracks: Dyeing, Inspection, and Full Process
The conference focused on three specific scenarios: digital transformation of dyeing enterprises, AI fabric inspection, and full-process digitalization. This selection is not random—dyeing is the most energy- and emission-intensive link, fabric inspection is the most labor-dependent quality control step, and full-process digitalization is the hardest nut for SMEs to crack.
Hangzhou Huanyu Digital Smart Technology showcased its TDSD® low-carbon digital dyeing process, which verified feasibility with data: nearly 99% water savings, 33% carbon reduction, and 21% fewer chemicals. The 'inkjet equipment + new ink materials + AI color management' system essentially transforms intermittent dyeing into continuous, on-demand flexible production. For buyers, this means more stable technical support for small-batch, fast-turnaround orders.
AI fabric inspection is another fiercely competitive track. Shanghai Kaiquan Intelligent Technology's 'teachable self-learning AI system' and Nantong Julian Digital's online defect warning and warp/weft density monitoring solutions both point to the same core logic: AI inspection cannot be a closed black box—it must connect with existing production management systems to form a 'detect-feedback-adjust' loop. Luo Yucheng, Deputy General Manager of Keqiao Weaving and Dyeing Industry Brain Operations, highlighted real challenges: algorithm adaptation for complex fabrics and cost barriers for SMEs remain hard thresholds for large-scale AI inspection adoption.
Keqiao Sample: From Point Application to System Integration
Sun Weigang, Director of the Keqiao Textile City Management Committee, revealed the '1+4+N' comprehensive intelligent agent system at the conference—a key sample for observing regional industrial belt digital transformation. This architecture attempts to solve a common dilemma: digital projects often stay at the point-application stage without achieving system effects. Keqiao's approach connects four major functional modules—market trading, information release, trend analysis, and supply chain services—through one comprehensive intelligent agent platform, then extends to N vertical scenarios.
The industry significance of this architecture lies in transforming digitalization from 'a company's own business' into 'a matter of industry chain collaboration.' When transaction, production, and logistics data can flow within one system, cross-link intelligent decision-making becomes truly possible. For foreign trade enterprises, this means full-chain traceability from order to shipment—a hard metric increasingly demanded by international brands during factory audits.