Personal Hygiene Product Packaging Inspection
Detect product damage or contamination under partly opaque plastic wrap
Graphical programming environment for deep learning-based industrial image analysis
Feminine hygiene products, infant diapers, pull-up diapers, adult incontinence products, and other personal care items are soft, easily deformed products that are case packed at high speeds. Packages typically contain many of the same item.
The packaging consists of opaque plastic or paper wrap printed with identifying and branding elements. Typical defects include packages that: are not completely closed; have some contents, such as a diaper, protrude through the seal to the exterior; or have contents extending over the seal but not to the outside.
These sealing defects need to be detected against a printed background that can be reflective, visually complex, or creased. When the contents are blocking the seal, but still inside the packaging, the only visible sign of the compromised seal might be a slight wrinkle. Such defects are hard for traditional rule-based machine vision to detect. Any flaws in the packaging, contamination, or damage to the contents of such personal products could keep a consumer from purchasing or repurchasing the product, which can harm brand value.
Cognex edge learning technology offers a valuable inspection solution for products with limited visibility and reflectivity. The defect detection tool trains on a set of images of acceptable personal hygiene product packaging conformations and shapes. The tool then identifies anomalous packages, while passing the full range of acceptable variations. The tool can quickly distinguish between purely cosmetic wrinkles and those that indicate a compromised seal. Packages with unacceptable seals are not packed on pallets and will not reach the end retailer, protecting brand value.
The defect detection tool retrains quickly with a new image set if there is any change in the printed branding or packaging arrangement and can be back in operation with minimal delay.
- Detect packaging flaws
- Recognize package contamination and defective package seals
- Preserve brand value