Our challenges
It has been observed that protein and carbon-hydrates in beer sometimes combine into
strings of protein, appearing as visible particles looking similar to spider webs known as
floaters. The development of floaters occurs after the bottles are sealed and is caused by
extended temperature changes and mechanical stress of the beer. It thus requires a quality
inspection of these particles inside individual bottles.
The impurity level of the beers was classified based on the number of detected particles and
the distribution of big and small particles. Consuming the particles is harmless. However, the
bigger floaters pose a serious consumer concern, whereas the small floaters are invisible to
the untrained eye.
Our solution
Previously, only trained personnel could classify the beers into different categories.
Nevertheless, this classification method is a subjective classification and is dependent on
various factors such as light, bottle colour, and bottle condition (scratches, etc).
To solve this issue, we developed a camera system that is able to classify beer based on
size distribution and quantity of floaters in the beer. The system rotated and illuminated the
beer bottles with a uniform backlight to observe the particles float fully unfold from a
360-degree scan.
This camera system allows us to detect developments of impurities and haziness by
calculating the particle size distribution and amount, which thus improved manual product
control previously applied in the beer production process.
Our challenges
Objective classification into xx number of classes
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Reduced manual labor and maintenance costs
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Guarantee reliability and process safety Sapphire optics and hygienic design
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