Bottle manufacturers produce billions of bottles every year. Let’s take the example of PET bottles - estimates suggest that 500 billion PET plastic bottles are manufactured annually!

Given the mammoth volume of bottles manufactured daily, monitoring quality becomes an arduous task. Manufacturers must scrutinize every detail—from cap tightness and tilt to label alignment and information accuracy. Additionally, they have to check for performance defects that could lead to leaks and poor bottle strength, packaging defects that cause inconsistencies like uneven thickness, and other quality flaws like wrinkles, bubbles, and base imperfections.

A thorough and meticulous inspection of each bottle is crucial because a minute oversight could have ripple effects in every industry, from pharmaceuticals to consumer goods that use bottles extensively.

That’s why a technology like Vision AI is essential. 

How Vision AI Works?

Vision AI uses high-resolution cameras, Artificial Intelligence (AI), and image processing AI models to monitor the bottle manufacturing process. 

The cameras capture high-resolution images of the bottles as they pass the conveyance belt, and the software processes them. The software compares the processed images with the dataset used to train the machine for defects like cap misalignments or labeling issues and flags the problem to enable workers to resolve it. 

From minor imperfections such as scratches to major ones like ill-fitting cap placements and label quality, Vision AI can inspect every aspect of manufacturing in real time and help bottle manufacturers improve product quality.

Take the time example of a leading beverage manufacturer. They used to inspect every bottle manually. This led to misaligned labels and contamination, affecting the product’s quality and damaging its reputation. They quickly resolved the problem by automating the inspection process using Vision AI. By incorporating AI-powered Vision AI with the existing OT/IT systems, the manufacturer automated the defect detection and inspection processes, minimized waste, and earned profits by consistently producing high-quality bottles.

Similarly, a study was conducted where the researchers developed a computer vision system to detect defects in liquid bottles. They used Complementary Metal Oxide Semiconductor (CMOS) cameras, conveyor belts, and software to identify the defects. The camera captured the images of the bottles on the conveyor belt, processed them using the software, and compared them with pre-defined standards to identify deviations and eliminate the defective bottles from the production line. The study showed that with computer vision, the company could inspect almost 7,200 bottles per hour and achieve an overall accuracy of 95.6% and 100% in liquid-level detection. 

Let’s Discuss Bottling Inspection with Vision AI

Here are some benefits of using Vision AI:

• Detect branding defects

Maintaining brand quality is a non-negotiable for bottle manufacturers. A minor label defect or color inconsistency could tarnish the brand’s reputation, lead to costly recalls, and attract regulatory fines. Typically, bottle manufacturers rely on workers to visually assess the bottles under standard lighting. However, such methods are subjective, error-prone, and inefficient, especially when thousands of bottles are produced every second.

Vision AI can automate the process and ensure high accuracy. Using high-resolution cameras, manufacturers can capture detailed, multi-angle images of each bottle. It can detect logo variations, alert the workers if the color or font varies from the defined brand guidelines, and allow them to analyze components in a detailed manner.

This prevents non-compliant bottles from being launched in the market and safeguards manufacturers from attracting heavy fines. 

• Address contamination concerns

Contamination is a huge concern for manufacturers as it can damage their reputation and attract fines. Take the example of Coca-Cola. In 2009, the beverage giant was fined Rs 1 lakh, and a consumer had to be paid a compensation of Rs 50,000 because the drink was contaminated, and the consumer fell sick after drinking it. Such incidents are common and could occur even if the manufacturers follow a fool-proof bottling system, as Coca-Cola did.

Vision AI can check for contamination risks early by examining the bottles for microscopic cracks and damages that are usually not visible to the human eye. It can analyze the captured images in real-time and segregate good and rejected bottles during production. This enables the manufacturer to remove the rejected bottles from the production line and ensure that only thoroughly evaluated bottles are sent to the market. 

• Solve capping and leakage issues

Like labeling, workers would traditionally check each cap manually to look for cracks, holes, color, misaligned liners, and seals. They would also use manual, hand-held tools like calipers and sometimes even rulers and measuring tapes to measure the caps' diameter, height, and dimensions. The method was susceptible to errors and exposed the bottle to contamination and leakages. 

Vision AI can detect these issues using cameras, specialized lights, and AI. It can accurately detect various defects, such as cap misalignment that leads to leakages, color deviation, missing caps that can result in contamination, titled and crooked caps, and cap height. This helps manufacturers prevent contamination and leakage and enhances the bottle’s quality and safety. 

How Vision Guard AI Can Help Manufacturers Maintain Consistent Quality

From scaling business to staying on schedule and ensuring manufacturing quality, manufacturers face many daily challenges. Clearly, traditional inspection methods are not a viable solution.

That’s why we recommend Vision AI to automate the manufacturer’s inspection process and help them maintain quality standards throughout the production cycle. 

Our AI-driven inspection solution, Vision Guard AI, can seamlessly fit into the manufacturer’s existing workflows, conduct real-time inspections, and pinpoint defects that could impact the quality of the product and lead to compliance and contamination issues.  

It helps manufacturers maintain consistent quality throughout every stage of bottle manufacturing.

To know more about Vision Guard AI, contact us.