The water-saving and carbon-reduction data in the dyeing process are reshaping industry awareness. The TDSD® low-carbon digital dyeing technology, launched by Hangzhou Huanyu Digital Smart Technology, achieves nearly 99% water savings, 33% carbon reduction, and 21% less chemical usage. Its 'spray-and-dye' model is built on a proprietary inkjet equipment, new ink materials, and an AI color management system. This data means that for dyeing enterprises aiming to cross the green threshold, the technical path has shifted from vague concepts to quantifiable, replicable engineering solutions.
Event Background
On May 7, the 2026 Textile Industry Digitalization Development Conference was held in Keqiao, Shaoxing, with the theme 'Smart Connect Textile Capital, Digital Create Future – Building New Quality Productivity in the Textile Industry.' Yan Yan, Vice President of the China National Textile and Apparel Council, noted that AI applications in textiles are rapidly moving from concept validation to large-scale deployment and outlined three major directions for the '15th Five-Year Plan' period: building a textile smart large model and vertical small models, breaking down data silos for cross-chain intelligent decision-making, and integrating green manufacturing to establish a full-chain carbon footprint tracking model. Sun Weigang, Deputy Secretary of the Keqiao China Textile City Party Working Committee, introduced the local '1+4+N' comprehensive intelligent system and the 'live streaming + platform + cross-border e-commerce + overseas warehouse' digital trade chain.
The conference focused on three core tracks: digital and intelligent transformation of dyeing enterprises, AI fabric inspection technology, and enterprise full-process digital upgrade. Hu Song, Director of the China Textile Information Center, released the 'Digital Intelligence Leading: High-Quality Development Transformation Roadmap for the Textile Industry in the 15th Five-Year Plan,' proposing a differentiated strategy where SMEs adopt low-cost, fast-result paths and large enterprises shift from system building to data ecosystem driving, summarized in a five-step method: diagnose status, select scenarios, supplement data, run pilots, and expand capabilities.
Industry Impact
From a practical perspective, the conference sent several key signals. First, digitalization in dyeing is no longer just a 'nice-to-have.' Long Fangsheng, General Manager of Meixinda Printing and Dyeing, proposed that digital factories should transform from cost centers to order creation centers, urging enterprises to move beyond simple fabric production and use digital upgrades to create incremental value. The water- and carbon-saving data of the TDSD process directly challenges traditional dyeing models, meaning that for dyeing clusters like Keqiao, Shengze, and Nantong, future capacity competition will increasingly depend on environmental compliance costs and flexible supply capabilities.
Second, AI fabric inspection technology is moving from labs to workshops. Shanghai Kaiquan Intelligent Technology showcased a full-chain AI vision system emphasizing 'teachable' self-learning; Nantong Julian Digital Technology launched multi-scenario solutions covering online defect warning, warp/weft density monitoring, and production anomaly detection. However, Luo Yucheng, Deputy General Manager of Shaoxing Keqiao Weaving and Dyeing Industry Brain, pointed out three bottlenecks: algorithm adaptation for complex fabrics, system instability in harsh environments, and high deployment costs for SMEs. The lack of a unified industry defect standard database is a fundamental barrier to large-scale AI inspection adoption.
Third, lightweight, incremental transformation paths gained more recognition. Wang Rong, CEO of Shaoxing Getaikesi Light Textile Technology, proposed that small and medium trading companies can achieve full-process digital closed loops via low-code platforms, following a 'point-to-area, small-step quick-run' path. This aligns with Hu Song's five-step method: start from the most painful scenario, the clearest data, and the most measurable benefit. For buyers, this means that a supplier's digital capability is no longer 'all or nothing' but can be verified through specific pain-point improvements.