One of the first ways in which artificial intelligence (AI) and machine learning are poised to have a positive and dynamic impact on the textile industry is through the widespread adoption of automated fabric inspection systems.
This is currently a trending topic in the industry, with the majority of leading mills around the world still relying on human inspection within their operations, according to Calvin Wong, CEO of Hong Kong-based AiDLab, the Laboratory for Artificial Intelligence in Design.
“In the next 10 years at least 50% of these manufacturers will be employing AI-based systems,” he said during the recent ITMAconnect Innovative Technologies webinar, which is now available to view in full at goto.itmaconnect.com. The latest camera-based vision systems for textile material inspection can eliminate defects, in addition to precisely verifying colour shades and achieve enormous savings.” He added that quality “will significantly reduce returns which are currently extremely costly to the industry and the environment”.
AiDLab is the developer of WiseEye, an AI-based textile material inspection technology that automatically and accurately detects fabric defects and colour shading at high speeds and in real-time inspection environments.
With the integration of machine vision algorithms and deep learning techniques, the system achieves an accuracy of over 90% and provides high-speed inspection at up to 60 metres per minute. The system also offers automatic defect labelling to meet industry requirements.
It can inspect various fabric types and identify over 40 common fabric defects.
Both Florian Pohlmeyer, head of digitalisation at RWTH Aachen University’s Institute for Textile Technology (ITA) and Sverker Evefall, senior application manager for Swedish vision systems developer ACG Eyetech, stressed the need for good data during the ITMAconnect webinar.
To prepare companies for the digital future, ITA opened the Innovation and Learning Center (ILC) in Aachen in 2017. In its Model Factory 4.0, digital solutions for production are being developed and via workshops and seminars, basic knowledge on the topic of Industry 4.0, condition monitoring, sensor technology and automation is provided to companies.
ACG EyeTech exploits 2D, 3D and deep learning techniques for inspection, measuring and robotic guidance. At ITMA 2023 in Milan, sister companies ACG Kinna and ACG Nowo demonstrated a complete process for robotic pillow filling with the ability to fill and finish some 3,840 pillows in an eight-hour shift. ACG EyeTech is now adding machine vision systems to these systems for fault-free and seamless fibre handling, filling, sewing and packing.
“Without qualitative data the most advanced machines will not achieve what they are fully capable of,” Pohlmeyer said.
“The textile industry has a complex value chain and many processes within it, and data which is collected at every stage is often unstructured or distributed across different software systems, databases and machines.
Each has its own format and it’s very important that they are standardised to enable systems to communicate.”
Evefall added that any vision system has to be shown what to do, like teaching a child.
“Don’t underestimate the time involved, because the algorithm is not an intelligent being that can just find defects, you actually have to teach it what to look for,” he said.
“Many manufacturers have the perception that AI can do everything but implementing it is an evolutionary process which takes time. The system has to be shown vast amounts of data.”
