Automated Plastic Cap Defect Inspection Using Machine Vision

Plastic caps are the most commonly seen bottle caps used in beverage and food containers. They are widely used to seal freshness of beverage or liquids in bottles. Threads are usually grooved inside the caps for easy twist-off caps and sealing rings prevent the liquids from bacterial infection. Companies print logos or pictures on the top surface of plastic cap, such that the quality of printing also indirectly affects the customers purchase. Inspection of plastic caps, including the surface printing, thread, and sealing ring, is a great issue during the caps production currently. The objective of this study is to use machine vision to inspect the defect of the sealing area and the printing surface of a plastic cap. An automated inspection system, which includes two CCD camera, lighting source, sensors, and a cap transporter, is constructed, and a digital image processing software is designed to learn good caps and screen out the defective ones. The experimental results show that the proposed inspection system can self-learn the features of a good surface printing, and effectively detect the defective caps under very few parameters setting, while the major defects in the sealing ring and thread area such as malformation, contamination, overfill, incomplete, scratches, can be successfully identified under the rate of 1,200 piece per minute.