Shell Button Inspection Machine

Automated detection system: Button automatic feeding is achieved through vibration discs, and industrial CCD cameras capture product images at millisecond speeds, combined with machine vision algorithms for real-time analysis.

Multi dimensional defect recognition: It can detect dimensional deviations such as length and outer diameter, as well as surface defects such as electroplating defects, scratches, cracks, burrs, damages, holes, etc. It also supports the recognition and verification of identification information such as logos and characters.

Intelligent sorting mechanism: equipped with a multi station detection module, it classifies and identifies the front and back sides, automatically eliminates non-conforming products, and outputs finished products that meet quality standards.

Detection accuracy: Using high-resolution industrial cameras and professional optical systems, the defect recognition accuracy reaches over 99.7%, far exceeding the level of manual detection.

Efficiency improvement: The detection speed can reach 1200 pieces per minute, achieving 24-hour continuous operation, which is 300% more efficient than traditional manual detection.

Quality control: Establish a digital defect database to support real-time statistics and analysis of detection data, providing data support for production process optimization.

Cost optimization: One time equipment investment can replace long-term labor costs, and single line testing can reduce 3-5 quality inspectors, resulting in a 45% reduction in overall costs.

Quality assurance: Ensure that the strength, wear resistance, and environmental stability of natural shell buttons meet the requirements of high-end clothing.

Capacity improvement: Automated testing throughout the entire process improves production line efficiency and shortens delivery cycles.

Brand value-added: Accurate defect control ensures product consistency and enhances end consumers' recognition of clothing quality.