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Textile Recognition and Sorting for Recycling at an Automated Line Using Near Infrared Spectroscopy

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Textile Recognition and Sorting for Recycling at an Automated Line Using Near Infrared Spectroscopy recycling Article Textile Recognition and Sorting for Recycling at an Automated Line Using Near Infrared Spectroscopy Kirsti Cura 1,*, Niko Rintala 1, Taina Kamppuri 2, Eetta Saarimäki 2 and Pirjo Heikkilä 2 1 Department of Technology, LAB University of Applied Sciences, Mukkulankatu 19, 15210 Lahti, Finland; niko.p.rintala@lab.fi 2 VTT Technology Research Centre of Finland, P.O. Box 1000, FI-02044 VTT Espoo, Finland; taina.kamppuri@vtt.fi (T.K.); eetta.saarimaki@vtt.fi (E.S.); pirjo.heikkila@vtt.fi (P.H.) * Correspondence: kirsti.cura@lab.fi Abstract: In order to add value to recycled textile material and to guarantee that the input material for recycling processes is of adequate quality, it is essential to be able to accurately recognise and sort items according to their material content. Therefore, there is a need for an economically viable and effective way to recognise and sort textile materials. Automated recognition and sorting lines provide a method for ensuring better quality of the fractions being recycled and thus enhance the availability of such fractions for recycling. The aim of this study was to deepen the understanding of NIR spectroscopy technology in the recognition of textile materials by studying the effects of structural fabric properties on the recognition. The identified properties of fabrics that led non-matching recognition were coating and finishing that lead different recognition of the material depending on the side facing the NIR analyser. In addition, very thin fabrics allowed NIRS to penetrate through the fabric and resulted in the non-matching recognition. Additionally, ageing was found to cause such chemical changes, especially in the spectra of cotton, that hampered the recognition. Citation: Cura, K.; Rintala, N.; Keywords: textile recycling; textile reuse; fibre recognition and sorting; automation; near infrared Kamppuri, T.; Saarimäki, E.; Heikkilä, spectroscopy; circular economy P. Textile Recognition and Sorting for Recycling at an Automated Line Using Near Infrared Spectroscopy. Recycling 2021, 6, 11. https:// 1. Introduction doi.org/10.3390/recycling6010011 Reusing and recycling discarded textiles are, in general, preferable waste management options to incineration and landfilling. In the environmental context, reusing products Academic Editor: Martin Schlummer has been shown to be preferable to recycling textile materials [1]. However, at some point Received: 29 October 2020 in its lifecycle, a textile product will be worn out or get dirty so it is no longer suitable Accepted: 28 January 2021 Published: 8 February 2021 for reuse. In this case, recycling may offer the material a new lifecycle. To add value to the recycled material and to guarantee that it has adequate quality as an input material Publisher’s Note: MDPI stays neutral for the subsequent recycling processes, it is essential to be able to recognise and sort the with regard to jurisdictional claims in item according to its material content [2]. Manual sorting of textile waste based on the published maps and institutional affil- fibre material content listed on product labels is possible but slow and often unreliable, iations. because the labels may have been removed, be worn out or have faulty information. According to a study by Circle Economy, up to 41% of labels on blended materials contain inaccurate information [3]. There are methods available for the identification of textile materials, such as ISO standardised quantification methods based on different dissolution behaviour (ISO 1833-1, etc.), morphological differences detected by microscopy [4], DNA Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. recognition [5] and differences in thermal behaviour detected by differential calorimetry, This article is an open access article thermogravimethic analysis and gas chromatography [6]. These are accurate, but require distributed under the terms and sample preparation and, as such, are too slow for automated recognition and sorting of conditions of the Creative Commons textile materials needed for recycling. Therefore, to enhance the use of recycled material, Attribution (CC BY) license (https:// there is a need for an economically viable and effective way to recognise and sort textile creativecommons.org/licenses/by/ materials. In NIR spectrometry (NIRS), sample preparation is not required, and it is 4.0/). widely used in industry for a variety of operations. Additionally, NIRS has been used in Recycling 2021, 6, 11. https://doi.org/10.3390/recycling6010011 https://www.mdpi.com/journal/recycling Recycling 2021, 6, x FOR PEER REVIEW 2 of 12 widely used in industry for a variety of operations. Additionally, NIRS has been used in Recycling 2021, 6, 11 textile identification, for example detection of cotton content in blend fabrics [7], analysing2 of 12 material contents in cotton polyester blends [8], identification of cashmere from other an- imal fibres [9] and determining the contents of four different materials (wool, polyester, polyacrylonitrile,textile identification, and nylon) for example at the detection same time of cotton [10]. content Hypers inpectral blend fabrics near infrared [7], analysing imaging has materialalso been contents used in in identifying cotton polyester polyester blends content [8], identification in blended oftextiles cashmere [11]. from other animalAutomated fibres [ 9recognition] and determining and sorting the contents lines ofprovide four different a method materials for ensuring (wool, polyester, better qual- ity ofpolyacrylonitrile, the fractions being and nylon) recycled at the and same thus time enhance [10]. Hyperspectral the availabili nearty of infrared such recycled imaging frac- tionshas with also accurately been usedin known identifying material polyester content. content The in t blendedwo best textiles-known [11 commercial]. or close Automated recognition and sorting lines provide a method for ensuring better quality to commercial automated recognition and sorting lines are FIBERSORT [12] by Valvan in of the fractions being recycled and thus enhance the availability of such recycled frac- the tionsNetherlands with accurately and SIPTex known [13] material in Sweden content. which The two uses best-known Tomra’s commercialNIR technology. or close A re- quirementto commercial for mandatory automated EU recognition-wide separate and sorting collection lines for are textile FIBERSORT waste [12by] European by Valvan Un- ion instarting the Netherlands from 2025 and[14] SIPTex will no [13 doubt] in Sweden accelerate which a transition uses Tomra’s towards NIR technology.cost-effective A tex- tile requirementsorting plants. for mandatoryHowever, to EU-wide our knowledge separate collection, this is the for first textile time waste that by chemical European struc- turalUnion modifications starting from research 2025 [14 of] willtextiles no doubt has been accelerate carried a transition out using towards NIRS at cost-effective the automated sortingtextile line. sorting plants. However, to our knowledge, this is the first time that chemical struc- turalLAB modifications University of research Applied of textilesSciences has has been developed carried out a usingmethod NIRS and at equipment the automated for the sorting line. recognition of textile fibre materials that can be used for research and development pur- LAB University of Applied Sciences has developed a method and equipment for poses for studying qualitative and quantitative textile fibre recognition. The recognition the recognition of textile fibre materials that can be used for research and development andpurposes sorting forlab studying pilot (REISKAtex) qualitative and identifies quantitative unknown textile fibre textile recognition. fibres by The comparing recognition their nearand-infrared sorting (NIR) lab pilot spectrum, (REISKAtex) wh identifiesich has been unknown mathematically textile fibres by processed comparing (normalisation their near- andinfrared second (NIR)derivative), spectrum, to a which validated has been material mathematically spectral library processed and (normalisationthen sorting the and iden- tifiedsecond samples derivative), using automated to a validated air material blowers spectral [15]. libraryA schematic and then picture sorting of the the identified lab pilot is depictedsamples in usingScheme automated 1. air blowers [15]. A schematic picture of the lab pilot is depicted in Scheme1. Scheme 1. The REISKAtex recognition and sorting lab pilot. Scheme 1. The REISKAtex recognition and sorting lab pilot. While NIRS offers benefits to material sorting, it has some limitations. For example, becauseWhile NIRS the electromagnetic offers benefits radiation to material of the sorting, used wavelengths it has some doeslimitations. not penetrate For example, the becausesample the effectively, electromagnetic thick layers radiation of other of materials the used on wavelengths the sample will does affect not recognition. penetrate the sampleThe aimeffectively, of this work thick was layers to gather of other understanding materials of on NIR the technology sample will in the affect recognition recognition. of Thetextile aim of materials this work and was especially to gather identify understanding reasons for non-matching of NIR technology recognition. in the The recognition work of textilewas carried materials out by and using especially over 250 fabrics,identify both reasons pre- andfor pre-consumernon-matching samples, recognition. which The were sorted using the lab pilot. Majority of the samples (73%)
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