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A pile of used clothing looks uniform at a glance, but it's actually a mix of cotton, polyester, wool, blends and dozens of other compositions – and that mix is exactly what makes textile recycling so dependent on accurate classification.
Textiles can only be recycled effectively once they're grouped by composition – a cotton garment and a polyester one need completely different recycling processes, and a blend of the two often needs a process of its own. Without that initial separation, recycling options narrow dramatically.
What makes textile recycling hard isn't a lack of recycling processes for individual fibre types – it's the difficulty of sorting a highly varied waste stream into those types quickly and accurately enough to feed those processes at scale. Manual sorting by composition is slow and inconsistent, especially with blended fabrics that aren't visually obvious.
With separate collection of textiles becoming mandatory across the EU by 2025, the volume of textile waste reaching sorting facilities is set to increase substantially – and that volume will need a sorting capacity that manual processes alone won't be able to match.
Artificial vision classification addresses this gap directly – using optical sensors to identify fabric composition and sort accordingly, at speeds that make separate textile collection viable as something more than just a collection exercise. PICVISA's experience in waste sorting and separation extends naturally into this growing area of textile recycling.
Get in touch with our team to discover how PICVISA's optical sorting and robotics solutions can fit your recycling operation.