Using AI to Preserve Your Personal Care Product Brand Promises

DL for Personal Care Products Large

Personal care product manufacturers rely on brand loyalty to achieve their market share targets. Consumers want to feel confident that products such as disposable diapers, facial tissue, toilet paper, cosmetics, and toothpaste are both well-made and safe to use. Consumer loyalty is granted in exchange for consistently high product quality that delivers on the brand promise. Even small flaws can damage customers’ trust, particularly when there are many competing brands.

Achieving high levels of quality requires inspection at various points in the production process. Inspection also plays a role in optimizing material costs, whether calculating the proper amount of material to be used or reducing waste associated with defective raw materials.

Demand for personal care products is rising which is pressuring manufacturers to run production lines at higher speeds , which require faster inspection methods.

Traditionally, human inspectors performed visual quality checks by examining a sample set of the overall production lot. Now, manufacturers need faster, more accurate, 100% inspection methods to keep up with quality and throughput.


As volumes increased, the initial approach to maintaining quality standards was to add more human inspectors. However, people are prone to making mistakes, use variable judgement, and tire quickly when performing repetitive tasks for many hours.

The labor shortage is another complicating factor which leaves manufacturers with two choices: 1) Reducing shifts to match available labor and thereby reducing overall equipment effectiveness (OEE) or 2) investing in automation to perform continuous in-line inspections and maintain production schedules.

Enter traditional rule-based machine vision. This automation technology provides a high-speed, cost-effective, and error-proof way to achieve 100% in-line inspection rates. These smart cameras and sensors are ideal for solving inspection challenges when the variables are known, for example, checking for presence or absence of a component, or checking to see if a label is aligned properly.

While rule-based machine vision solves predictable inspections, there are often unpredictable defects that are too complex to solve with human inspectors or rule-based algorithms. These include contaminants and rips in packaging that vary by location, shape, and size, as well as complex branding elements and material types. So how do you solve these challenges?


Fortunately, artificial intelligence (AI) has found its way into advanced manufacturing practices across a variety of industries, including personal care products. Cognex AI-based tools in vision systems and software automate defect detection, classification, and code reading applications that are too challenging for traditional machine vision alone.

Using AI ensures that primary and secondary packaging contain no structural, cosmetic, or printing defects, and that their contents are complete, damage-free, and meet quality standards.

Here are several examples of how AI-powered inspections help preserve brand value, increase OEE, and reduce costs.


Consumer product manufacturers must print or emboss date and lot codes on certain products for end-to-end traceability. Codes can become distorted by shiny materials and curved packaging.

OCR code reading on squeeze tube seals and aerosol cans


OCR code reading


Cognex’s AI-based OCR tool easily reads codes on challenging curved, textured, and reflective surfaces, even at high speeds, increasing throughput and OEE.



Product quality inspections prior to packaging are critical to ensure completeness, maintain customer satisfaction, and protect brand reputation. Detecting size, shape, color, texture, portioning, and fill level defects prior to shipping protects your company’s reputation against the net effect of damaged goods while avoiding stoppages and downtime. Inspecting soft personal hygiene products such as diapers or feminine care products can be particularly challenging due to high line speeds and the use of printed backgrounds.

High-speed inspection of soft personal hygiene products


Personal Hygiene DL inspections


Cognex AI technology checks the outer layers distinguishing between defects and the colored designs or branding.


A critical quality step in the manufacturing process of personal care products is primary packaging inspection. Common applications include correct item placement, foreign materials, proper sealing, proper labelling, and readability of any regulatory tracking codes.

Personal hygiene packaging



Personal hygiene packaging inspection

Flexible, reflective, and highly branded product packaging create inspection challenges for traditional rule-based machined vision.

Cognex AI-based software quickly identifies packaging defects, even with ambiguous backgrounds. The defect detection tool trains on an image set of defect-free packages and can distinguish between true packaging defects or minor wrinkles.

Cosmetic adhesive label inspection

Cosmetic label inspection

Each label on cosmetic jars must be inspected for bubbles, tears, wrinkles, or other defects. Any number of defects can appear anywhere on the label making it difficult to inspect with traditional rule-based machine vision.

Cognex’s In-Sight 2800 vision system uses AI-based tools to detect anomalies and can quickly be retrained if the label design or shape changes, minimizing machine downtime and increasing OEE.

Inspecting cosmetic containers for foreign bodies

Cosmetic Container inspection

Cosmetic jars for beauty creams and moisturizers may be contaminated with dust particles, fabric, or insect parts and must be inspected prior to filling. These foreign bodies are often hard to distinguish from the jar itself due to background material color and reflections from industrial lighting.

Using the combination of Cognex High Dynamic Range Plus (HDR+) technology and AI software, defects and contaminants in cosmetic jars are easily discovered prior to filling, ensuring optimal brand experience.

High-speed inspection of products with reflective packaging

Razor packaging inspection

Packages containing many small personal care products, such as razors or electric toothbrush heads, must be inspected to validate they contain the correct quantity, type, and arrangement. The stiff plastic outer packaging is often transparent and reflective, making it difficult to confirm the package contents.

Using the combination of Cognex High Dynamic Range Plus (HDR+) technology and AI tools, the contents of these types of packages can easily be validated to improve product quality and line efficiency.

Squeeze tube sealing inspection

Squeeze tube sealing

Seals on squeeze tubes must be inspected to prevent leakage or contamination. Due to the wide variation of seal defects and the tolerance of minor irregularities, traditional rule-based machine vision is not an ideal choice for automated inspection.

Cognex AI-based inspections distinguish between acceptable and unacceptable seals by learning from a set of images of both good and bad seals. Identifying defects while tolerating minor acceptable anomalies helps manufacturers improve throughput while delivering high quality products to their consumers.


AI-based inspection is an exciting, emerging technology that offers a cost-effective, scalable solution to the current labor market challenges and yields fast return on investment. Learn more about how investing in AI increases production efficiency, reduces the costs of excess raw material, and prevents defective finished products from reaching store shelves.



Junte-se ao MyCognex