| Availability: | |
|---|---|
| Quantity: | |
HY-S580
Product Introduction
The HY-S580 single side label visual inspection system machine is designed for automated quality inspection of garment labels and textile labels. Equipped with a high-definition industrial camera and a built-in AI inspection system, it detects common label defects, including surface stains, pattern misalignment, text defects, color variations, uneven edges, missing sections, and broken yarns. The system works with downstream equipment to automatically reject defective labels, helping manufacturers improve inspection efficiency, maintain consistent product quality, and reduce manual inspection workload. It supports a variety of label types, with inspection speed and label dimensions configured according to the application and compatible equipment.
Product Advantage
1. AI-Powered Label Defect Detection
The built-in AI inspection system identifies common visual defects on label surfaces, including stains, text imperfections, pattern misalignment, color variations, and missing sections. It provides an automated approach to label quality inspection, helping manufacturers reduce reliance on manual visual checks.
2. High-Definition Industrial Camera
Equipped with a high-definition industrial camera, the system captures label images for visual analysis. It is designed to inspect printed patterns, text, edges, and surface conditions across different label styles. Inspection settings can be configured according to label characteristics and production requirements.
3. Automatic Rejection of Defective Labels
The inspection system works with compatible downstream equipment to remove labels identified as defective. This integrated inspection and rejection process helps reduce the circulation of nonconforming labels and supports more consistent quality control throughout production.
4. Inspection Speed of Up to 200 Pieces per Minute
The machine offers a stated inspection speed of 0–200 pieces per minute, depending on operating conditions and the configuration of the production line. This makes it suitable for manufacturers looking to automate label inspection and improve production workflow efficiency.
5. Flexible Label Size Compatibility
The standard inspection range covers labels approximately 10–60 mm wide and 35–170 mm long. Actual compatible dimensions may vary depending on the downstream equipment and machine configuration. This flexibility allows the system to be adapted to different label formats and production applications.
Technical Parameters
Vision Inspection Speed | 0-200 pcs/min |
Label Width | 10-60mm |
Label Length | 35-170mm |
Dimension | 1200L×1000W×1750H(mm) |
Weight | 120KG |
Voltage | 220V AC 50Hz |
Power | 0.5KW |
Product Uses
1. Garment and Apparel Labels
Suitable for inspecting clothing labels used in shirts, jackets, trousers, sportswear, and other apparel. The system helps identify surface stains, text defects, pattern misalignment, and edge irregularities before labels proceed to the next production stage.
2. Woven and Textile Labels
Designed for quality inspection of woven labels and other textile labels. It can help detect visible defects such as broken yarns, missing sections, uneven edges, and irregular label dimensions, supporting more consistent label quality.
3. Printed Brand and Care Labels
Suitable for inspecting printed brand labels, size labels, and care labels. The AI inspection system checks visible text, patterns, and surface conditions to help identify printing defects and appearance inconsistencies.
4. Automated Label Production Lines
The machine can be integrated with compatible downstream equipment for automatic rejection of defective labels. It is suitable for label manufacturers seeking to incorporate machine vision inspection and automated quality control into their production workflows.
How to Operate the AI Label Inspection Machine
Prepare the machine: Check the camera, lighting, inspection software, and connections with compatible downstream equipment.
Set up the inspection program: Configure the inspection parameters according to the label type, dimensions, patterns, and text.
Run a sample test: Feed sample labels through the machine and verify that common defects can be identified correctly.
Start inspection: Run the production line at a suitable speed, up to the specified maximum of 200 pieces per minute.
Check rejection performance: Confirm that defective labels are correctly rejected by the connected equipment and adjust settings when necessary.
Actual setup procedures may vary depending on the machine configuration and production line.
FAQ
Q1: What defects can this AI label inspection machine detect?
The system is designed to identify common visible label defects, including surface stains, missing sections, uneven edges, pattern misalignment, text defects, color variations, and broken yarns. Actual detection performance depends on the label material, defect characteristics, image quality, and inspection settings.
Q2: What is the maximum inspection speed?
The specified inspection speed is 0–200 pieces per minute. Actual operating speed depends on the label type, inspection requirements, production conditions, and compatible downstream equipment.
Q3: What label sizes can the machine inspect?
The stated inspection range is 10–60 mm in width and 35–170 mm in length. These dimensions may vary depending on the machine configuration and the downstream equipment used. Please provide your label dimensions for compatibility confirmation.
Q4: Can the machine automatically remove defective labels?
Yes. The inspection system works with compatible downstream equipment to reject labels identified as defective. The specific rejection mechanism and integration requirements depend on the production line configuration.
Q5: Can the machine inspect different types of labels?
The system supports various label types, including woven and printed labels, subject to compatibility testing. For an accurate recommendation, please provide label samples or clear images, label dimensions, common defect examples, and your required production speed.