AI quality control continues textile's history of automation

The textile industry was at the heart of the Industrial Revolution, and with the introduction of the programmable Jacquard loom, was arguably the first industry to be automated (the loom was the distant ancestor of modern computers). Researchers at Hong Kong Polytechnic University (PolyU) have now applied artificial intelligence to textile manufacture, installing machine vision into looms as an intelligent fabric defect detection system.

Known as WiseEye, the system uses deep learning to detect up to 40 common fabric defects with an accuracy resolution of 0.1mm/pixel, minimising the chances of producing substandard fabric by up to 90 per cent. Currently, quality control in textile production is done by humans inspecting random lengths of fabric by eye, and fatigue and simple error mean that this is unreliable and inconsistent.

“In view of the numerous fabric structures that give great variations in fabric texture and defect types, automatic fabric defect detection has been a challenging and unaccomplished mission in the past two decades,” said research leader Prof Calvin Wong of PolyU’s Institute of textiles and clothing.