Cutting-Edge Fabric Identification: SWIR Spectroscopy and Sorting Techniques for Post Processing

The textile industry faces a critical challenge in efficiently identifying and sorting materials composed of diverse fiber blends during recycling and valorization processes. Traditional reflectance spectroscopy, a common technique for high-speed sorting, primarily captures information about dyes and treatments applied to the material, limiting its ability to assess the intrinsic chemical composition of different fibers.

To address this limitation, we explore the potential of short-wave infrared (SWIR) spectroscopy, a technique renowned for its effectiveness in distinguishing plastic types. Given the prevalence of synthetic fibers in textiles, Ferland focuses on the SWIR system's ability to differentiate between synthetic and vegetal fibers.

Ferland’s findings reveal that SWIR systems can rapidly and accurately distinguish multiple types of fibers and blends, even in dark-colored materials, a known challenge in the industry. Furthermore, she employs a hyperspectral scanner operating within the 1.0 to 2.5-micrometer range to precisely characterize fiber concentrations in blended fabrics.

To enhance the identification process further, Ferland evaluates various post-processing and analysis algorithms, optimizing the characterization of fabric samples. Results holding significant promise for implementing this process on an industrial scale, potentially revolutionizing the textile recycling sector, are provided.

The research enables high-speed identification of various fiber types and blends, offering essential insights for fabric recycling and paving the way for a more sustainable and environmentally conscious textile industry.

About the presenter
With over 15 years of experience in business development in a high-tech environment, Marie-Christine Ferland is responsible for bringing in new business, exploring and evaluating the potential of new markets, and managing key accounts at Photon etc.