On-line Detector Equipment Cap Inspection System to Check False Accepts

Inspection standard

In actual testing, due to the critical fluctuation state of certain testing items, it will lead to a certain probability of product misdetection. According to the actual operation of the equipment, the false detection rate is about 0.2%. The product error can be reduced by the second retest Check.

Details are as follows:

Inspection rinciple

Through the waterfall conveying system, the 5~15mm caps is stably and orderly conveyed to the specific station in the same orientation, and then the high-pixel image taken by the industrial camera is transferred to the image processing software, and compared with the standardized model, after analysis determine the good and defected products, blowing the defected caps collecting the good caps. Meanwhile, the good caps will be counting and binning. The counting accuracy rate is within the range of N~(N+10).

The software will open the sample comparison standard, and the QC staff can control the comparison accuracy and choose the accuracy standard most suitable for their own production conditions, thereby controlling the defect rate.

Testing details

The inspection system equipped with 11 sets of high-pixel industrial cameras and high-performance stroboscopic light sources to conduct a full range of visual inspections for the appearance of bottle cap products. The inspection speed can reach 400 pieces per minute, and the machine can achieve 7*24 hours. The defected caps can be automatically rejected .

The whole inspection system includes material sorting equipment, mechanical structure, visual electronic hardware and testing system software, which can be independently arranged on the customer site, and can be equipped with dust removal, disinfection and other production line equipment according to the specific production needs of the customer on the site.

real-time image

CONTAMINTION- detectable

Cavity number - detectable

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