Advanced sorting technologies
Advanced sorting technologies refer to innovative and technologically advanced systems and processes used to sort and categorize fashion products for the purpose of digital recycling and upcycling. These technologies leverage cutting-edge methods, such as machine vision, artificial intelligence, and data analytics, to efficiently and accurately identify, classify, and separate garments and materials based on their suitability for recycling or upcycling.
Digital recycling and upcycling involve the transformation of discarded or unused fashion products into new, valuable items through digital processes. Advanced sorting technologies play a crucial role in this context by enabling the automated identification and separation of materials that can be recycled or repurposed, thereby streamlining the digital recycling and upcycling workflows.
One of the key components of advanced sorting technologies for digital recycling and upcycling is the use of machine vision systems. These systems employ cameras, sensors, and advanced image recognition algorithms to capture detailed visual information about fashion products. Through machine vision, these technologies can identify specific garment types, materials, colors, patterns, and other attributes that are relevant for determining their recycling or upcycling potential.
Furthermore, advanced sorting technologies integrate artificial intelligence and data analytics capabilities. By analyzing vast amounts of data, including historical records, product specifications, and material characteristics, these technologies can learn and improve their sorting accuracy over time. They can identify patterns, trends, and correlations that help in making informed decisions regarding the recycling or upcycling potential of fashion items.
The benefits of advanced sorting technologies in the context of digital recycling and upcycling are significant. They enable the efficient and precise sorting of fashion products, reducing the reliance on manual labor and minimizing errors. This not only saves time but also enhances the overall quality and value of the recycled or upcycled materials.
Moreover, these technologies contribute to the circular economy in the fashion industry. By facilitating the identification and separation of recyclable or upcyclable materials, they support the transition from a linear “take-make-dispose” model to a more sustainable and circular approach. Advanced sorting technologies promote resource efficiency, waste reduction, and the reuse of materials, thereby reducing the environmental impact associated with fashion production and utilization.
Case studies
Reverse Resources – Textile-to-textile waste mapping platform
Reverse Resources provides a digital platform that maps textile production waste and post-industrial leftovers, classifying them by fibre type, quality, and location. By standardising data on waste streams and connecting manufacturers with recyclers, the platform enables more accurate “virtual sorting” before physical handling, improving feedstock quality for recycling and reducing the need for manual pre-sorting.
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Sysav – Siptex automated textile sorting plant
Siptex, operated by Swedish waste company Sysav, is an industrial-scale automated textile-sorting facility that uses near-infrared (NIR) spectroscopy and machine vision to sort post-consumer textiles by fibre composition and colour. The plant demonstrates how large-scale automated sorting can create high-quality feedstock for fibre-to-fibre recycling and reuse markets, significantly increasing throughput compared to manual sorting.
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Fibersort (Circle Economy & partners) – NIR-based post-consumer textile sorting
Fibersort is an automated sorting technology that uses NIR spectroscopy to identify fibre composition and sort post-consumer textiles into dozens of fractions suitable for recycling and reuse. Developed with partners including Circle Economy and Valvan, Fibersort shows how advanced optical sorting can handle high volumes of mixed textiles, creating consistent material streams that enable mechanical and chemical recyclers to scale.
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Matoha – FabriTell handheld NIR fabric analyser
Matoha’s FabriTell devices use NIR spectroscopy to identify fibre composition in textiles within seconds, supporting both industrial sorters and smaller collectors. By providing reliable, on-site fibre identification (e.g. cotton vs. polyester vs. blends), these handheld and desktop instruments allow more accurate material separation, reduce contamination in recycling streams, and support data collection for digital sorting and grading systems.
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TextileGenesis – Digital fibre-to-retail traceability platform
TextileGenesis offers a blockchain-based traceability platform that assigns digital tokens to fibre and material flows, enabling granular tracking of textiles from fibre production through to finished garments. While not a physical sorter, the platform underpins “data sorting” by certifying origins, fibre types, and transaction histories, allowing brands, recyclers, and sorters to distinguish and prioritise materials that meet specific circularity or recycling criteria.
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References
Charnley, F., et al. (2022). Can digital technologies increase consumer acceptance of circular business models? The case of second hand fashion. Sustainability, 14(8), 4589. https://doi.org/10.3390/su14084589
Colombi, C., & D’Itria, E. (2023). Fashion digital transformation: Innovating business models toward circular economy and sustainability. Sustainability, 15(6), 4942. https://doi.org/10.3390/su15064942
Juanga-Labayen, J. P., et al. (2022). A review on textile recycling practices and challenges. Textiles, 2(2), 174–188. https://doi.org/10.3390/textiles2010010
Bonifazi, G., et al. (2022). End-of-life textile recognition in a circular economy perspective: A methodological approach based on near infrared spectroscopy. Sustainability, 14(16), 10249. https://doi.org/10.3390/su141610249
Akhtar, W. H., et al. (2022). A new perspective on the textile and apparel industry in the digital transformation era. Textiles, 2(4), 633–656. https://doi.org/10.3390/textiles2040037