Identification of fibre composition of apparel for recycling

Communications in Development and Assembling of Textile Products, 2021

The application of the principles of sustainable fashion is one of the solutions to reduce the amount of waste from textile production and the use of such fabrics. Spectrophotometric methods have effective application in this subject area. In the present work, an analysis of known methods and approaches applied so far using the techniques of spectral analysis. The proposed methods and procedures lead to improvement and facilitation of the process of classification of textile fibers in sorting and recycling of textile fabrics, in order to implement in automated systems. The proposed analysis tools do not require high cost equipment and complex calculation procedures. They can be implemented in portable devices and microprocessor-based recognition systems. It has been found that two principal components and two latent variables are sufficient to describe the variance in the data. This significantly reduces the amount of data used to analyze textile fibers by their spectral characteris...

Introduction-stakeholder identification 3 End of life management 3.1 Legislative drivers-National and EU legislations 3.2 End-of-life management of textiles and corporatewear: financial motives. 3.3 End-of-life management of textiles and corporatewear: new marketing opportunities-"green" image. 4 Product labels and eco-labels 4.1 Objectives of product labelling 4.2 Eco-labelling systems 4.3 Voluntary labels for the textiles, clothing and footwear sectors 4.4 Standards and criteria used by eco-labels 4.5 Fair trade 5 Product labels indicating EoL management 5.1 Cradle to cradle (C2C) 5.2 EcoMate 5.3 The EU 'Flower' Ecolabel 5.4 Cradle to Cradle 5.5 Costs of eco-labelling 6 Potential developments for eco-labels with EoL management criteria 6.1 Royal Mail Group 6.2 Stakeholder analysis ~ risks/benefits 7 Conclusions 7.1 Considered options-use of existing labelling 8 Recommendations 9 References Appendix ©Centre for Remanufacturing & Reuse

Sustainability

For the textile industry to become sustainable, knowledge of the origin and production of resources is an important theme. It is expected that recycled feedstock will form a significant part of future resources to be used. Textile recycling (especially post-consumer waste) is still in its infancy and will be a major challenge in the coming years. Three fundamental problems hamper a better understanding of the developments on textile recycling: the current classification of textile fibres (natural or manufactured) does not support textile recycling, there is no standard definition of textile recycling technologies, and there is a lack of clear communication about the technological progress (by industry and brands) and benefits of textile recycling from a consumer perspective. This may hamper the much-needed further development of textile recycling. This paper presents a new fibre classification based on chemical groups and bonds that form the backbone of the polymers of which the fib...

Fashion and Textiles, 2020

What guarantees are there in buying one of the most frequently purchased products? Considered unanimously as the first modern industrial activity, the textile sector was introduced into Spain in the nineteenth century. At that date, Spain was a country mainly centered on agriculture, with the exception of Catalonia and the Basque Country as the first two industrialized regions. In its beginnings, the textile production was dominated by its artisanal nature, being manufactured from natural materials such as lamb's wool, linen or cotton. Nowadays, Spain is among the top major world powers in fashion. 1 The fashion sector advances with giant steps and this is possible thanks to the internationalization of local firms, innovation in buying-selling channels, the originality of the materials and processes, strategic alliances and service quality (Gumbau 1998; Coll and Blasco 2009; Sojo 2012; Kosińska et al. 2014) Concerning the textile sector, the labelling requires a particular study, being an aspect of great relevance and which is in the spotlight: labelling is the most effective way of linking with the consumer the maker's indications regarding the

This paper is a collective review on the different methods available to recycle textile wastes namely composting, paper making, techniques adopted by fashion brands to recycle old clothing. Special focus is given to technical textiles, composites and non-woven sectors that involve product development using up cycled wastes. This can be an eye-opener to researchers and industrialist's worldwide to indulge in more research activities and serve in reducing the landfill pollution.

Data in Brief, 2024

The utilization of computer vision techniques has significantly enhanced the automation processes across various industries, including textile manufacturing, agriculture, and information technology. Specifically, in the domain of textile manufacturing, these techniques have revolutionized the detection of fiber defects and the quantification of cotton content in fabrics. Traditionally, the assessment of cotton percentages was a labor-intensive and time-consuming process that relied heavily on manual testing methods. However, the adoption of computer vision approaches requires a comprehensive dataset of fabric samples, each with a known cot- ton percentage, to serve as training data for machine learn- ing models. This paper introduces a novel dataset comprising 1300 original images, covering a wide range of cotton percentages across thirteen distinct categories, from 30% to 99%. By employing image augmentation techniques, such as rotation, horizontal flip, vertical flip, width shift, height shift, shear range, and zooming, this dataset has been expanded to include a total of 27,300 images, thereby enhancing its utility for training and validating computer vision models aimed at accurately determining cotton content in fabrics. Through the extraction of pertinent features from the images of fabrics, this dataset holds the potential to significantly improve the accuracy and efficiency of computer vision-based cotton percentage detection.

2017

The aim of the Trash-2-Cash project is to explore and pave way for a design-driven methodology in the development of textile-to-textile recycling processes. Within the Trash-2-Cash project, a sub-target has been to analyse the potential for automated sorting of post-consumer textiles. This has resulted in this report focusing on NIR technology to become an important automated online tool for an increased sorting quality for textile recycling. The work has included experiments on sorting, and the outcomes of these studies are described here with the exception of some technical details which are restricted from public view due to binding obligations in the project's Grant Agreement for the protection of intellectual property rights. At present, the sorting of post-consumer garment and household textile waste for recycling has limited accuracy. Manual sorting relies to a large extent on label information attached to the garment and such information is often missing in collected goods. Erroneous labels and human errors in the manual sorting add to the difficulties of achieving the requested quality. A central issue is whether the quality requirements of the recycling processes can be met. This is especially critical for textile-to-textile recycling, which generally requires high-quality sorted textile waste fractions. Potential chemical fibre recycling processes, such as the key processes within the Trash-2-Cash project, are likely to need high quality-sorted fractions of post-consumer textile waste to produce new textiles. Provided that a material recognition technology can sort for textile-to-textile applications, this technology would be a promising solution for the textile sorting industry. This study endeavours to assess the current state and the potential of automated near-infrared (NIR) technology as a material recognition technology for sorting towards higher quality. The NIR technology is still under development for textile sorting and a fully automated system has not yet been demonstrated and validated. Performance tests have been conducted as part of this study during the period from May 2016 to February 2017 on four NIR units. Based on the observations from the testing, the potential capability of the automated NIR technology to improve the sorting is discussed. Based on the test observations, garments made of pure fibre types/groups such as cotton, polyester, polyamide, acrylic, wool, man-made cellulosic or silk were identified, as well as cotton and polyester blends. Some blends presented larger difficulties and were more frequently unidentified. In particular, blends with a low content of a minor fibre constituent were often unrecognised, mainly blends with elastane. Further observed difficulties for the automated NIR sorting are blend garments were the fabric exposes different fibre types and composition on the inside than on the outside. The potential of NIR sorting is very large if it is integrated properly, but many unanswered questions remain regarding its ability to meet performance requirements and the acceptable levels of contamination for recyclers. These challenges can not only be met by improvements in the sorting system; there is also a call for designing for circularity, especially considering fibre blends during product development.

Recycling

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 throug...

2019

This paper identifies an opportunity to design a localised textile waste system in New Zealand which provides the raw material required to develop a value added, closed loop, innovative and sustainable textile product. Sustainability is a key challenge of our time. The mass production processes of the apparel industry create large volumes of waste posing significant sustainability issues at all levels. New Zealand is a wasteful country that has up until recently managed textile waste recycling by exporting or landfilling the problem. Ministry for the Environment records indicate 100 million kilos of textile waste is disposed of into New Zealand’s landfill annually. At present options for unwanted textile waste in New Zealand are limited. The emergent crisis of textile waste stream management requires systems change and new forms of collaboration to be researched, designed and actuated. This paper challenges some of the complexities surrounding an unsustainable manufacturing cycle an...