Robotic IV-bag inspection line

IV-bag fully automatic inspection line supported by Deep Learning Artificial Intelligence (AI)




PBL Pharma Division has designed and built an innovative and flexible Inspection line for IV Bags.
The main goal was to create a machine capable of performing different types of automatic inspection (by cameras and supported by Artificial Intelligence). Particles control, cosmetic control, closure control, and barcode reader are some of the controls installed.
Artificial Intelligence is the core of our machine: it allows to obtain an extremely accurate inspection of particle and cosmetic defects, and thus to overcome many past issues and/or false rejects (such as air bubbles, silk-screening on containers, aesthetic defects of the containers that are considered non-relevant).
The extremely compact design, combined with the handling flexibility provided by a robot, makes ROBOX a unique and modular machine.

Main features

⦁ Robotic automatic bag loading system
⦁ First station for automatic inspection
⦁ Rear and/or radiant light illuminator
⦁ Second station for automatic inspection

More features

⦁ Barcode reader
⦁ Inspection software supported by Deep Learning and Artificial Intelligence (Patented)
⦁ Robotic automatic rejection
⦁ Robotic automatic bag unloading system

Machine Output

15 to 300 BpM

Compatible containers


Deep Learning
and Artificial Intelligence

A novel inspection machine has been designed and developed with the use of a specifically designed cellular neural network (CNN) coupled with an off-the-shelf neural network trainable solution. The novel machine, thanks to the computational versatility of the CNN, is capable of reaching high standards of assessment drastically decreasing the risk of operator-based errors during production.

The dedicated CNN developed by PBL is composed of two parts:
⦁ a first network that has the scope to perform a defined series of image processing steps in order to enhance the features of the objects that have to be detected.
⦁ a second network that is responsible for the feature extraction of the different defect classes that the network is trained to detect

With this dedicated configuration, PBL was able to developed a customized Artificial Intelligence solution for all the different types of inspection machines of its customers.

In addition, it is important to highlight that the neural networks developed by PBL can be trained off-the-shelf, thus ensuring a stable software solution that does not evolve in time, unless the user decides to modify the software.

Artificial Intelligence Technology

Thanks to our proprietary AI-technology we are able to offer the unmatched ability to recognize, in real time, the presence of particle defects and leaks in both rigids and flexible containers.

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