AOI High Precision Accuracy Visual Inspection System For Fresh Food Tray

Inspection principle

KEYE TECH inspection machine adopts deep learning + visual inspection technology, combined with automatic control technology, and has the functions of automatic sensing, automatic detection, automatic recording and elimination of unqualified products. It can also be seamlessly connected to the existing molding machine without redundant modification. Instead of manual inspection of appearance defects such as dirt and damage of products. While reducing labor costs, it greatly improves efficiency and is more accurate and stable. It can be widely used in the detection of food and drug plastic packaging materials.

Advantages of ai algorithm

• Accuracy of results: Compared with traditional vision algorithms, the stability of deep learning algorithms is greatly improved, and it can adapt to general disturbances in the environment and background. At the same time, the accuracy of the algorithm is also higher than that of traditional vision algorithms;
• Algorithm versatility: For different defects, only a small number of defect samples need to be collected. After sufficient training, different defect samples can be automatically identified. The algorithm adopted is a unified algorithm framework;
• Development timeliness: Since there is no need to develop algorithms for different defects, the entire development cycle is greatly shortened, and general visual defect projects only need 2-3 hours to go online for testing;
• Environmental reliability: Due to the guarantee of GPU computing power, the entire system can work in a high-temperature environment for a long time with sufficient computing power margin.

Advantages of big data cloud platform

• The model has wide applicability: by distinguishing whether there is a template or not, it can basically cover the detection requirements of surface defects, and new defect models can be added arbitrarily;
• The robustness of the model is good: through the system signal consistency adjustment, it is basically guaranteed that there is no need for fine-tuning on site, and it can run normally when it goes online;
• Fewer training samples are required: In the case where a large number of defect samples cannot be obtained, the automatic synthesis of samples can be used to meet the needs of deep learning with large data volume training samples;
• Fast model reasoning speed: Control the cost of model deployment, and provide customers with a cost-effective deployment platform as much as possible on the premise of meeting the needs.

After-sale service

The company has a complete technical service team and rapid response mechanism, and has dedicated service specialists for each customer, who can receive technical consultation and fault reports from customers at any time. And to ensure rapid response to customer emergencies, to ensure that customers receive satisfactory service.During the epidemic or due to special reasons, when after-sales engineers are unable to reach the site, the service center can remotely adjust customer equipment for troubleshooting and technical consultation.

After the equipment arrives at the customer site, the after-sales engineer arrives in time to carry out equipment installation, commissioning, and operation training. The product quality of the whole machine is traceable, and the quality warranty period is 1 year from the date of acceptance. In the event of non-human faults during the warranty period, after-sales engineers will quickly arrive at the site or provide remote guidance for free maintenance.

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