Forecasting Recycles Textiles: Exploring structure, composition and colour data to forecast the sorting and design of recycled yarns

This paper explores the required data for companies to understand the value of their textile wastes for the sorting/design of recycled fibres. Sustainable fashion forecasting is a relatively new field which has mainly focused on how better forecasting can avoid the generation of waste. However, this research focuses on forecasting the waste itself for sorters/designers developing recycled yarns.
The paper unfolds a case study of the laundry company: Elis (as part of Decouple project in the Trace Partnership). Using mixed methods, comprising data analysis and practice-based design prototyping, data from Elis’ current circulating workwear was combined with physical examples of Elis’ waste textiles from their recycling partner to create a recycled forecast. This was achieved by narrowing the data to suitable
garments for recycling and collecting their colour, structure and composition details to understand the feedstock potential. This data was used to sort the textile waste examples, and after shredding, design various combinations into prototypes (non-woven swatches) to visualise the possible recycled coloured fibres and create a roadmap of how this waste could be best sorted/recycled. The paper concludes that
colour, structure and composition data points are vital in providing forecasting value for companies, sorters, recyclers and designers in the transition towards circular textiles.