Perfectly sealed: How intelligent technology ensures 100% quality

Quality starts with the seal

Sealing is often the final step in the packaging process – and one of the most important. Only a flawless seal seam can reliably protect the contents until they reach the end customer. This is especially true for sensitive products in industries such as hygiene or pharmaceuticals, where intact packaging is essential to ensure product quality, shelf life, and safety. Defective seals, on the other hand, can have serious consequences – from product damage to costly complaints.

Accordingly, a common question in practice is: How can 100% sealing quality be ensured?

A key factor is the systematic inspection of the seal seam directly on the production line. Today, this step goes far beyond simple defect detection – it also enables targeted root cause analysis. This forms the foundation for precise process control and sustainable improvement.
 

Thermography as the key to fault detection

To assess seal quality, a combination of advanced technologies is used. Thermal imaging cameras accurately measure the temperature distribution along the seal seam. High-resolution image sensors provide a detailed view of the seal pattern. The collected data is then analyzed using intelligent algorithms and compared against defined reference patterns.

This makes it possible to reliably identify deviations – such as cold seal seams, faulty side folds, or irregularities in the seal pattern. The combination of thermography and image processing delivers consistent and reliable results, even when dealing with varying packaging materials or changing recipes.
 

From fault detection to process optimization

This method provides consistent and traceable results – even across different packaging formats and materials. Its major strength lies in more than just fault detection, it allows for precise classification. The analysis delivers clear insights into where and why an issue has occurred. This transparency significantly enhances responsiveness during production. Based on this, targeted corrective actions can be derived – such as adjusting temperature profiles or sealing times.

The solution is already being used successfully in real-world applications. Further development is underway to explore how artificial intelligence could be used more effectively – for instance, to automatically recommend suitable corrective actions or suggest process improvements.

As a result, quality control is becoming more closely integrated into the production process. It is no longer viewed as a downstream step, but as an active component of process control – ensuring long-term, reliable product quality.