A single data point is rewriting the competitive rules of China's garment manufacturing: when fabric utilization exceeds 95%, custom production is no longer a cost black hole.
Jiangsu Sunshine Group was recently selected for the 2026 list of provincial-level advanced smart factories in Jiangsu. Using its self-developed AI algorithms, the company achieved fabric utilization above 95%, shortened order delivery cycles by 35%, and boosted overall production efficiency by 30%. These figures reveal how technology is systematically dismantling the structural pain points of traditional custom garment manufacturing: high variety, small batches, short lead times, and fragmented demand.
From Experience-Driven to Algorithm-Driven
Custom garment production has long relied on the experience of master craftsmen, with pattern design, fabric cutting, and production scheduling all handled manually. This leads to low efficiency, difficulty in standardization, and unstable delivery. Sunshine Group's response is a five-layer digital architecture: device IoT, data middle platform, business collaboration, digital twin, and intelligent decision-making. This is not a simple addition of IT systems but a fundamental restructuring of the production system from the ground up.
Within this architecture, 3D digital pattern design replaces manual pattern making, AI virtual fitting reduces repeated sampling, 3D laser body scanning captures body measurements in milliseconds, and AI visual inspection replaces human quality checks. The key is the global intelligent scheduling system, which uses algorithms to dynamically assign orders to different production lines, allowing small personalized orders and large batch orders to coexist flexibly.
This means factories no longer need to choose between 'efficiency' and 'flexibility.' Previously, custom orders often led to equipment utilization rates below 60% due to complex processes and frequent line changes. Sunshine Group's scheduling system reduces changeover times to minutes, enabling 12 interconnected smart production units to operate in coordination.
The Path to Flexible Manufacturing
Public industry data shows that capacity utilization for China's garment industry hovers around 75%, while custom factories typically operate below 60%. Sunshine Group's 'material-to-worker' flexible logistics model is a key innovation addressing this issue.
Traditional production lines follow a 'worker-to-material' model—workers must go to the warehouse to fetch materials before returning to their stations. Sunshine Group uses AGVs to deliver materials precisely to workstations based on scheduling commands, allowing workers to focus solely on processing. This model reduces material handling time by over 40% and cuts work-in-process inventory.
On the quality front, the factory has built a full-lifecycle digital quality traceability platform. Data from raw material entry to finished product shipment is recorded and linked to specific orders and operators. A supplier dynamic control system adjusts procurement strategies based on historical quality data, reducing overall procurement costs.
Implications for the Supply Chain
What does Sunshine Group's practice mean for the textile industry? First, it validates the commercial viability of 'AI + textiles.' Previously, many companies believed AI in custom garment manufacturing was too costly with long payback periods. Sunshine Group's data shows that when fabric utilization rises from the industry average of 85% to 95%, material cost savings alone reach about 10%, enough to cover the investment in smart transformation.
Second, this case provides a replicable technical template for high-variety, small-batch orders. Foreign trade orders are increasingly fragmented, with single-order quantities dropping from thousands to hundreds of pieces and lead times shrinking from 60 to 30 days. Sunshine Group's five-layer architecture and flexible logistics can be directly transferred to other mid-sized garment factories.
Finally, the model is also relevant for home textiles and industrial textiles, which face similar customization demands. Digital twin and intelligent scheduling technologies can be applied across product categories.