Using Machine Vision to eliminate chance of human error in packing

About the project

We have collaborated with Astotec to build and internal visual quality control system.






Machine learning / Digital product development

Business type:



The employees working at these workstations need to place 20-25 cm (8-10 inch) long parts in container boxes. The layout of these boxes and the varying amount of parts cause a higher chance of human error.

It’s not uncommon that the amount of parts in the boxes are incorrect, and this can only be discovered when the end user opens the delivered packages.


We record the work process on video (10 FPS is sufficient). The Machine Vision tool checks the frames in real time, and operates an ‘OK – NOT OK’ binary feedback display on the workstation.

This means that the personnel working at the workstation always have realtime information about whether the amount of parts in the box are appropriate. This eliminates the possibility of human error.

The system features two AI models. The first one recognizes the type of the box, which means it knows the amount of required parts. It also checks if the complete box is visible, or partly covered. When the box is visible and the type is identified, it passes the number of required parts to the second model.

The second AI model is an object detection model, which counts the parts and checks it against the information coming from the first model. When the part count is right, it switches the display to ‘OK’. The shapes of the parts have been taught to the system, this is what it’s looking for on the image frames and counts the number of target objects on each frame.


The end result is an archived dataset, which logs the workstation, the time, and the feedback signal on the display. This makes the work process completely verifiable.

The main value though is the support it offers to the workers, basically eliminating the chance for this kind of human error at the workstation.

The whole solution can be built ‘on premise’, off-grid, and standalone, without outside internet access. This provides a sealed environment for complete data security, which often serves as added value in industrial environments.

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