Plastic Bottle Caps Full Automated Optical Visual Inspection System
Inspection Standard
| Model | Number of camera | Inspect | Inspection content | Precision | Speed |
| KVIS | 1 set | Concave area | Black spot,stains (color different) | ≥0.2mm | 800-1000 Pcs/mins |
| 1 set | Top area | Black spot,stains (color different) | ≥0.2mm |
| 4 set | Side area | Black spot,stains (color different) | ≥0.2mm |
| Printing missing | ≥1.0mm |
| Injection incomplete | ≥0.5mm |
| Sealing not good | ≥1.0mm |
4 set |
Ring area | Black spot, stains (color different) | ≥0.2mm |
| Incomplete | ≥0.5mm |
Inspection principle
For beverage, pharmaceutical, food and other manufacturers, the appearance defect of bottle caps is a common problem in the manufacturing process of products. Due to the increasingly high requirements for product packaging refinement, quality and continuous mass production, traditional manual inspection is easy to cause leakage. Inspection and false inspection lead to the outflow of defective products and low efficiency. The market poses new challenges to the original quality inspection of bottle caps.
The emergence of the AI-based fully automatic bottle cap visual inspection system has solved this difficulty well and has become a new choice for more and more industrial enterprises. The bottle cap inspection system can not only ensure the quality of packaging, but also detect the material of the bottle cap, avoiding the entry of materials that do not meet food safety standards into the production process, and ensuring the quality and safety of beverages and foods.
Inspection details
Based on computer vision and pattern recognition theory, adopts oscillating feeding method, equipped with AI deep learning system, uses CCD industrial camera to obtain online images of bottle caps in real time, and conducts multi-angle and multi-directional inspections on both sides, inside and side of bottle caps Shooting, determine whether it meets the requirements through image positioning and analysis, select bottle caps with defects in appearance, and realize online rejection of defective products to improve industrial production technology.
Hardware platform
◆ The main control platform adopts standard industrial computer, with vision acquisition board and signal control board.
◆ The industrial camera adopts high-precision mega-pixel industrial cameras such as CCD and CCD.
◆ Camera lens: Industrial lenses such as fixed focus and adjustable focus are used.
◆ Light source: optional white light, red light, blue light, infrared; surface light source, strip light, coaxial light, ring light.
◆ Algorithm design: use OpenCV and other design modules.
Test content
The detection position can be selected from the top surface, bottom surface, and inner/outer wall circumference of the bottle cap.
◆ Cap positioning: presence or absence, slanted cap, screw cap, double cap, cap height, round cap, reverse cap
◆ Cap mixing: color, printing (misplaced pattern, wrong printing), code, embossing
◆ Cap direction: align with product packaging or label
◆ Appearance of bottle cap: Dirty, lack of material, black spot, flash, wrinkle, extrusion
◆ Mixed bottle caps: According to the rapid modeling and variety management of different products, count the detection results and automatically eliminate waste products.
Company profile
KEYETECH has always been committed to the application of artificial intelligence in the field of vision technology, replacing human eyes and brain decision with machine vision and AI reasoning calculations, and integrating the quality detection and sorting to industrial products in traditional manufacturing to make the production more digitization , Intelligence, visualization, and persistence. Also greatly improves the efficiency and accuracy of industrial detection, and enhances the intelligent level of the manufacturing industry.
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Plastic Bottle Caps Optical Visual Inspection System Full Automated Images
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