TEXIA – Intelligent Inspection of Textile Knits with Artificial Intelligence
Project Description
TEXIA focuses on the research and development of a solution based on Machine Learning, computer vision and TinyML to automate the inspection of textile knits, with the ability to robustly detect and classify defects. The project addresses critical challenges such as the need to unify ML models, create more detailed defect classification (finer labeling), produce visual defect mappings to support decision-making, and ensure integration with production software. In terms of technological maturity, the project aims to evolve solutions currently at intermediate development levels towards validation and demonstration in an industrial context, reinforcing the digitalisation and modernisation of quality control in the textile sector.
General Objective
To develop and demonstrate an intelligent textile knit inspection solution based on AI, designed for use in an industrial environment, supporting detection, classification and decision-making in an integrated way
Expected Outcomes
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Technology demonstration in an operational environment (TRL evolution up to industrial demonstration levels)
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Greater efficiency and consistency in defect detection
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Reduction of waste and rework
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Strengthened competitiveness and digitalisation capacity of quality control
Funding
Total Cost: 890,432.40 €
Eligible: 890,432.40 €
Incentive: 570,204.66 €
End date: 2025-01-01
Start date: 2026-12-31
