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AI-enabled Textile Quality Control based on Consumer Hardware

Thomas Achim Schmeyer; Kai Krämer; Sven Pultar; Ali Nazeri; Christiane Plociennik; Martin Ruskowski
In: 11th IFAC Conference on Manufacturing Modelling, Management and Control MIM 2025. IFAC Conference on Manufacturing Modelling, Management and Control (MIM-2025), June 30 - July 3, Trondheim, Norway, Elsevier, Amsterdam, Netherlands, 2025.

Abstract

This paper presents a novel, low-cost, and accessible AI-based quality control test bench solution for the textile industry. It is especially designed for small and medium-sized enterprises. Using available consumer hardware and innovative AI techniques, the proposed system offers highly accurate quality control without significant financial investment. The developed software libraries, hardware documentation, and design are published as open-source projects on GitHub. The proposed approach is intended to empower small and medium-sized enterprises to install and implement advanced automatic quality control at low cost. The effectiveness of this approach has been validated within the K¨ostler Green-AI Hub pilot project.

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