As a proud member of the TCBL (Textile & Clothing Business Labs) network, we deeply valued the chance to connect with like-minded companies, exchange ideas, and explore collaborations that will help shape a more sustainable fashion industry.

“The TCBL network made us realize that we are not alone – together we can push the boundaries of sustainable fashion,” said Caterina Ailiesei, Founder of Katty Fashion.

A highlight of our participation was the Day 3 roundtable discussion on bio-based materials and the future of fashion, hosted by Messe Frankfurt. You can watch the full talk on Messe Frankfurt’s YouTube channel

During the three-day event, Katty Fashion’s team not only presented its own sustainable manufacturing practices but also learned from others’ breakthroughs. By engaging with cutting-edge textile and fashion companies and established innovators, we gained fresh perspectives on topics like textile recycling, bio-based fabrics, and supply chain transparency. These interactions have sparked ideas for new R&D projects and reinforced Katty Fashion’s belief that open collaboration is key to a greener, more efficient fashion industry.

Potential clients and partners visiting the Katty Fashion stand were able to see first-hand how the company’s agile, on-demand production model using 3D prototyping solutions and zero-waste strategies can add value to their collections. Many remarked on the advantage of working with a manufacturer that is both highly experienced and relentlessly innovation-driven, qualities Katty Fashion has honed through its 20+ years in business and active involvement in initiatives like TCBL.

AVANTEX reaffirmed our belief that innovation thrives through collaboration. We return inspired and motivated to turn the ideas and partnerships sparked in Paris into concrete projects for our clients and partners.

Sorting returned and no longer used collected garments is repetitive, strenuous, and tiring for workers. The introduction of a collaborative robot assistant (cobot), which combines image processing sensors, grippers, and artificial intelligence, represents a viable alternative. It is also expected to positively impact the distribution of second-hand items on the fashion market and the possibility of affordable business models with a limited environmental footprint.

CoboSort: recognizing, gripping, discarding, and learning
CoboSort focuses on developing machine learning models and robotic grippers and their integration into a reliable and comprehensive collaborative robot system. This enables automated picking to support the sorting of fully, partially or unpacked garments. “This is becoming increasingly important in times of online retail because returns are generated in large quantities and are often no longer properly packaged,” reports Olaf Kähler from DIGITAL. An intelligent image recognition system including AI for recognition and a gripper system for gripping the garments work together. All of this takes place in an environment in which humans and robots work together directly. “Our institute’s contribution is the software, the ‘brain’ so to speak, which tells the robot arm where to reach next,” continues Kähler. “The difficulty here is that items of clothing are soft and – if they are not packed in a plastic bag like new items – cannot simply be gripped with a suction gripper. It is also important that garments are picked up individually and placed on the conveyor belt, as double gripping can lead to a backlog later on.”

Environmentally friendly business models
The collaborative robot system sorts mixed and randomly arranged clothing packages, requires little space, is modular, and safe and its functions can be reconfigured. Compared to current sorting solutions, it represents a moderate investment and paves the way for decentralized and flexible redistribution systems that support the emergence of new forms of e-commerce for unused or previously worn garments and recycling. By reducing the continuous production of new garments, the impact on the environment is also reduced.

Change in the fashion industry
This new approach enables synergies between fashion companies and end customers, reducing the production costs of garments and indirectly reducing raw material consumption and waste. Positive effects can also be expected in social terms: instead of performing repetitive, wear-and-tear activities, the labor force is given a proactive role. Using an intuitive interface that can also be operated by non- experts, they train the machine learning models and support the cobot in the event of an error. Major international fashion chains have already shown interest.

Further information:
Dr Olaf Kähler
JOANNEUM RESEARCH DIGITAL
Steyrergasse 17, 8010 Graz

Tel: +43 664 602 876 2035
Mail: olaf.kaehler@joanneum.at