AI-Driven Sorting Technology Hits a Turning Point for Secondhand Garments: Swedish Machinery Maker Debuts New Module at Texprocess

The secondhand garment market is undergoing a technology-driven transformation at its very foundation. At the recently concluded Texprocess exhibition in Frankfurt, Eton Systems, a member of the Swedish textile machinery association TMAS, showcased its new aUPS module, whose core value lies in using artificial intelligence to solve the long-standing efficiency bottleneck of sorting used clothing.

Event Background

The aUPS module is not an experimental project starting from scratch. It is built on Eton’s widely deployed UPS material handling system, which powers automated overhead conveyor lines in hundreds of garment factories worldwide. The new module is driven by Eton’s ETONingenious AI platform, which can identify and classify garments in real time as they pass through the system.

Based on information released at the fair, the aUPS module has a clear market positioning: high-speed sorting of secondhand garments. This means its target customers are no longer limited to traditional apparel manufacturers but extend to the rapidly expanding sectors of used-garment recyclers, refurbishers, and brands’ reverse logistics operations.

This technology path is a direct response to the explosive growth of the secondhand clothing market. Industry public data show that global secondhand apparel trade has maintained double-digit growth over the past five years, yet the sorting stage remains heavily dependent on manual labor—costly and limited in accuracy. Eton’s AI sorting module is seizing the opportunity created by this supply-demand gap.

Industry Impact

For the textile industry, the AI-driven sorting of used garments has implications far beyond the sorting process itself. It is effectively paving a complete chain from old-clothing collection to recycled fiber production.

First, improved sorting efficiency directly lowers the cost of recirculating secondhand garments. For fast-fashion brands and resale platforms, this means more low-value garments can be economically recovered rather than landfilled. For recycled fiber suppliers, more precise sorting yields cleaner feedstock, which directly determines the quality and price of recycled yarns.

Second, this technology trend is reshaping the profit distribution within the secondhand garment supply chain. In the past, the sorting bottleneck limited the throughput of the entire chain, causing large volumes of old clothing to accumulate. Once AI sorting equipment can operate at speeds comparable to manual labor but at a lower unit cost, upstream recyclers will gain greater bargaining power, while downstream brands may secure a more stable supply of recycled raw materials.

From a regional industrial cluster perspective, this technology also holds relevance for China’s textile hubs. In clusters like Keqiao, Shengze, and Nantong—centers for chemical fibers and fabrics—the source of recycled fiber feedstock is expanding from industrial waste to post-consumer textiles. The introduction of AI sorting equipment will help these regions reduce their dependence on imported sorted feedstock and enhance the autonomy of their local supply chains.

Practical Recommendations

For Buyers - When evaluating used-garment sorting equipment, prioritize the alignment between the AI model’s training data volume and real-world scenarios, rather than just demonstrated accuracy. Eton’s aUPS module benefits from years of data accumulated through its garment conveyor systems, which is its core moat. - Consider the modularity of the sorting equipment. If future needs include handling more complex garment types (e.g., those with zippers or metal buttons), modular expandability is more important than a one-time investment.

For Foreign Trade Enterprises - Monitor the upcoming EU regulations on the mandatory sorting of textile waste. Once enacted, demand for efficient sorting equipment in the European market will surge, and products like Eton’s aUPS may face order backlogs. Locking in production capacity early or seeking alternative suppliers is a prudent move. - When exporting recycled fibers to Europe, providing proof of AI-sorted feedstock will significantly enhance product bargaining power, as brands are increasingly strict about raw material purity traceability.