Online with Capping Machine 1881 Cap Closures Visual Inspection System

Online with Capping Machine 1881 Cap Closures Visual Inspection System

Inspection Standards

Machine vision inspection product types are the mainstream intelligent products in industrial production. The product category recognition system is based on computer vision and pattern recognition theory. By acquiring product images, processing and analyzing the images, extracting characteristic parameters reflecting the morphological structure of product varieties, and then using the characteristic parameters to perform feature matching on corresponding products, so as to achieve Product category visual identity.

Product Background

Due to the enourmous speed of a closure production line and high quality requirements, closure inspection can be a challenging task. During production, common defects like contamination, flash, short shots and defects at the tamper evident band might occur. Our closure vision systems detect these defects effortlessly. In addition, the quality inspection of our systems include many other common and customized inspection criteria like color, cavity number reading, print control, laser engravings, high voltage micro-hole tests, diameter and height inspection.

No matter whether you produce standard closures or specialty caps like sports caps or push-pull caps, we offer different solutions for any kind of product. Even tethered caps do not present a problem since our inspection system is already prepared for the new EU regulation by means of special tethered cap inspection features.

Inspection Principle

The AI inspection system integrates lid feeding and handing equipment, conveying mechanism, visual system hardware and inspection software, and defective product rejection device. The maximum inspection speed is about 30,000 pieces/hour, and the equipment can achieve 7*24 It runs 24 hours a day, which greatly improves production efficiency.

The inspection equipment is equipped with a total of 6 sets of high-pixel industrial cameras to comprehensively detect the appearance of defects of the product. After the system collects sample images, the image processing software is compared with standardized samples to determine good and defective products, and the defective products are automatically eliminated online. , The software will open the sample comparison standard, and the production personnel on the customer site can control the comparison accuracy and choose the accuracy standard most suitable for their own production conditions, thereby controlling the defect rate.

Our Advantages

• 1. AI algorithm: high stability, adapting to the environment and background disturbance; different defect samples can be automatically identified after training
• Dataization: Independent database, save multiple samples, analyze non-good products, and retain history
• Multi-orientation: 360 ° comprehensive inside and outside the samples
• High precision: detection accuracy can be high
• Modularization, can flexibly increase or decrease the detection function according to customer actual needs
• Easy to operate: It is easy to operate and easy to maintain
• Safety: Medical grade material manufacturing, fully compliant with medical supplies production environment

After Sales Service

The seller should complete the creation and debugging of the product basic algorithm model before the equipment is shipped, also provide remote assistance after the equipment arrives at the customer site; and provide buyer with the factory data and operation manual of equipment.

Daily operation and maintenance services: Our company provides free remote operation and maintenance online services. If you need to upgrade inspection algorithm, provide operational assistance, etc.

Our company have regular offline training plan every year, so domestic and foreign clients can send their engineers to participate (at their own expense). Those who pass the exam can obtain an industry functional skills certificate.

About Us

Development History

The technology center is composed of algorithm department, software department, optics department, hardware department and mechanical department. The algorithm team currently has 7 PhDs, ensuring that the AI algorithm has the ability to continuously update.

Organization Structure