Reliable automation of FFP2 mask production with AI quality inspection

November 16, 2021

With the use of Vision AI, automatic optical inspection systems (AOIs) offer reliable quality assurance in production for versatile and complex tasks. At the same time, AI inspection systems from Data Spree can be flexibly trained quickly and reliably for each individual defect pattern.

Medical masks such as the FFP2 mask still play a keyrole in the strategy against the COVID-19 pandemic. To ensure sufficient productquality and protective function, the masks must be inspected for various typesof defects. Reliable automated inline inspection guarantees efficient processes and consistently high quality for the customer.

Traditional solutions are overwhelmed by complex requirements

Conventional sensor and image processing systems are often only designed for a specific task or have to be programmed from scratch in a very complex way. Algorithms are often developed by hand, which requires a lot of know-how and time. Complex tasks, such as different or difficult defect patterns, cannot be handled at all or only with great difficulty using these classic solutions. This often leads to high costs and to the fact that quality requirements can often not be completely fulfilled.

Reliably detect all errors in the production process using Vision AI

With AI-based visual inspection systems, the quality assurance process can be automated reliably and quickly inline and exline. The AI can learn to detect, classify and localize different types of defects and deviations. Thus, an optical system can simultaneously identify surface defects, material defects, printing and labeling defects or other processing errors in the ongoing production process. A powerful computing unit enables reliable use at high production speeds and short cycle times.

Figure 1 - Automatic visual AI inspection of FFP2 masks for various defect patterns: Print image, nose clip, strap attachment

The AI simultaneously inspects the mask material, which is processed as web material, at 6 inspection points in the production process: 4 band attachments, nose clip and imprint. In Figure 1, a faulty attachment for an ear band is detected, localized and is declared as a reject. By machine reading the time stamp, the defect can be clearly assigned. With the help of AI, any deviations from the target state can thus be identified, localized and communicated to the machine control system in real time. All possible defect types are thus reliably detected via a single AI-based inspection unit. Conventional sensors or simple camera systems are unable to handle this degree of complexity with a single camera system.

Figure 2 - The AI detects and locates a missing nose clip (left) and a faulty print image (right)

How also you can use the potential of AI in your production

AI-based automated optical inspection (AOI) solutions have the ability to quickly learn and effectively remediate defect patterns of any complexity. The flexibility of AI logic allows the potential of intelligent quality assurance to be harnessed for any type of product, component or surface across different products and industries.

Data Spree offers individually trainable AI inspection solutions for any type of application and task, as well as full integration into the machine environment. Data Spree's own software environment Deep Learning DS offers all possibilities of data management, AI training and evaluation in a simple user interface. With this optimized AI workflow, reliable and individualized inspection solutions are quickly ready for use and raise production quality to a whole new level.

Here you can find more information about our AI quality assurance solutions: 

More information about the Data Spree AI platform Deep Learning DS:


Do you need advice by our experts? Please contact us by e-mail at

Let's talk about your project.
Adopt one of our ready-to-use solutions, start creating your deep-learning-based system, or tell us your requirements to let us build an individual application for you.