A traditional garment customization factory has pushed its fabric utilization rate to over 95% while compressing order delivery time by one-third—a figure that reflects a systematic rethinking of intelligent manufacturing in the textile industry.
Event Background
The Jiangsu Provincial Department of Industry and Information Technology recently released the 2026 Jiangsu Provincial Advanced Intelligent Factory Candidate List, which includes Jiangsu Sunshine Group. This recognition is not merely an honorary title but an official endorsement of the company's substantive breakthroughs in addressing common industry pain points. For years, the garment manufacturing sector—especially customization—has been plagued by structural challenges such as high variety, low volume, short lead times, and fragmented demand. Traditional customized production suffers from low efficiency, difficulty in standardization, and unstable delivery, squeezing profit margins.
Architecture Restructuring: From Experience-Driven to Data-Driven
Sunshine Group's strategy was not to patch individual links but to rebuild the production system from the ground up. The factory established a five-layer digital architecture: device IoT, data middle platform, business collaboration, digital twin, and intelligent decision-making. The value of this architecture lies in connecting information flows that were previously scattered across measurement, pattern making, cutting, sewing, quality inspection, and warehousing, making data the core driver of production decisions.
In practice, the factory deeply integrates 3D digital pattern design, AI virtual fitting, 3D laser body measurement, AI visual quality inspection, global intelligent scheduling, and full-scenario digital twins. These technologies are not isolated but integrated into an end-to-end intelligent production system that spans from customer requirement collection to finished product delivery. When a customer places an order, the system automatically generates an intelligent pattern and sends instructions directly to the automated production line, achieving a closed-loop operation.
Data Validation: Efficiency and Flexibility Achieved
The results are significant. Using self-developed AI optimization algorithms, fabric utilization exceeds 95%—a high level in customized garment production, where pattern variations make traditional nesting inefficient. Order delivery time has been reduced by 35%, and overall production efficiency has increased by 30%. These figures translate directly into cost advantages and delivery capabilities.
More importantly, the factory has achieved a breakthrough in flexible manufacturing. It has built 12 interconnected and collaborative intelligent production units and implemented a "material-to-worker" flexible logistics model. This allows the production line to switch seamlessly between personalized small-batch, quick-response orders and large-volume group orders without frequent line reconfiguration. For buyers, this means shorter lead times, lower minimum order quantities, and more consistent quality.
Quality Control: Full Traceability
In lean management, Sunshine Group has established a full-lifecycle digital quality traceability platform and a dynamic supplier control system. From raw material sourcing to production inspection and after-sales service, all data is traceable and controllable. This effectively reduces procurement costs and significantly cuts inventory. For downstream brands and buyers, it means greater supply chain transparency and risk control.
Industry Implications: Balancing Customization and Scale
Sunshine Group's case offers an important lesson: customization and scale are not irreconcilable. When the digital architecture is robust enough, personalized production can be as efficient as standardized production. This model has direct implications for textile clusters—such as those in the Jiangsu-Zhejiang-Shanghai region—that are transitioning to high-end, customized production.