DataHub:
Connecting Digital Tools
in Textiles and Fashion
2025 - 2027
Development Project
TEKO Foundation
Co-Applicant
Summary
The Swedish School of Textiles at the University of Borås is undertaking a significant initiative to enhance its digital capabilities across research, education, and industry within the textile value chain. The vision for the next 7-10 years is to develop supportive and decision-making tools and systems for a more sustainable textile industry and value chain.
To achieve this, the project aims to establish an infrastructure to deal with extensive data from the textile components and processes, as well as supporting data reflecting the operators and the environment of the textile production. The textile labs at the University of Borås will serve as a test bed for data collection for years to come. Moreover, set-ups and methodology will be developed and shared to support textile companies interested in collecting their own data.
Based on the expanding future dataset, we lay the foundation for implementing AI and machine learning (ML) throughout the textile value chain.
Activities
The project investigates the possibilities of implementing a data infrastructure with regards to the following activities:
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Digital printing for increased quality of data collection in the form of images for detecting uniformity in the fabric.
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An advanced multi-sensor data acquisition system for weaving environments to collect comprehensive, high-resolution datasets. These will be curated and separated for analysis and development of a digital twin of the operator.
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The fibre and yarn environment, we to collect high-resolution, real-time data on key physical and visual parameters. This comprehensive dataset will form the foundation for AI-assisted prototyping and predictive modelling of textile structures.
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Adaptive archives as a resource for future design processes. The data collection will comprise of adaptive file formats, containing complex and interrelated information of form, texture, colour, movement, and composition.
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Cleaned and standardised data is crucial for analysis, especially in textile management, where primary and secondary data are combined to study the entire textile value chain.
Team
Niina Hernandéz
Prof. Nawar Kadi
As. Prof. Junchun Yu
As. Prof. Vijay Kumar
Jan Tepe
Mattias Bräck
Project Leader
Member
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Funding Organisation
