Automated Sewing System Enabled by Machine Vision for Smart Garment Manufacturing

This paper presents an automated sewing system designed for smart garment manufacturing, incorporating ma- chine vision capabilities into a custom-built sewing machine. The vision system captures an image of the fabric pattern placed between two acrylic plates with a small opening, utilizing a deep learning model to detect and segment the opening, which represents the area of interest on the plate. Subsequently, a specialized algorithm detects a narrow seam line within the segmented image and generates a stitching path alongside the seam line, ensuring a consistent distance. The sewing machine then accurately stitches along the generated path automatically. The vision system utilized in this study achieves a spatial resolution of 68 μm per pixel. The custom-built sewing machine, controlled by an external computer, exhibits a spatial resolution of 10 μm, a translation speed of 60 mm/s, and an adjustable stitching interval ranging from 1 mm to 5 mm. The subsystems and components are interconnected using the Robot Operating System (ROS), enabling seamless communication and integra- tion. The proposed system eliminates the need for human intervention, facilitating automated garment production. This innovative system is expected to play a critical role in realizing the vision of smart garment manufacturing.