Automated Sewbot to make 800,000 adidas T-shirts daily
Consistent data for SMV calculation accuracy.
5th January 2026
Innovation in Textiles
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Suzhou, China
Suzhou Tianyuan Garments, a leading manufacturer of high-quality sportswear for global brands such as Adidas, Anta, Fila and The North Face, has made notable productivity and cost management improvements following its implementation of Coats Digital’s method-time-cost optimisation solution, GSDCost.
Through the digitisation of its production processes, Tianyuan has improved SMV (standard minute value) calculation accuracy to 98%, shortened new product process analysis time from four days to one, and reduced sample garment development cycles by 25%.
The company employs over 5,000 people and produces more than 26 million garments annually.
“Before adopting GSDCost, our SMV calculations were largely based on the individual experience of engineers, resulting in variations of up to 30% across production lines,” said Tianyuan industrial engineering director Hailan Chen. “The lack of consistent data meant that process analysis for new products could take several days, often producing inaccurate results. The increasing need for faster turnarounds and more fragmented, complex orders highlighted the necessity for a more agile, scientific approach.”

The implementation of GSDCost has played a pivotal role in achieving the company’s strategic goals of higher transparency, efficiency and profitability.
“The standardised operation library in GSDCost also helped us reduce sample garment development cycles by 25%, securing a critical competitive advantage in an increasingly demanding market,” said Chen. “By digitizing the entire process from order placement to shipment, we have achieved major breakthroughs. It has become the core engine driving our transformation to smart manufacturing.”
GSDCost supports a more collaborative, transparent and sustainable supply chain in which brands and manufacturers establish and optimise ‘international standard time benchmarks’ using standard motion codes and predetermined times. This shared framework supports accurate cost prediction, fact-based negotiation and a more efficient garment manufacturing process, while concurrently delivering on CSR commitments.
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