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Quality Control in textiles at Sioen Veranneman

Veranneman, a Sioen Industries affiliate, used to rely on expensive machines to check mistakes or holes in the woven technical textiles. The Quality Control consisted of both an industrial machine check and secondly by employees. 

The current quality machines were not only costly hardware but also had a steep cost of ownership as it required much technical expertise. For instance, it required programming for every additional type of textile.

Solution

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RVAI3
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Initial data capture set–up
to gather data to train a model

Labeling and training in our RVAI platform

Testing the AI model on new data
from the data capture set-up

The solution Robovision and Viu More created, allows Sioen to optimize their Quality Control using deep learning-based fault detection. Robovision.ai trained the AI model that detects the anomalies in the textile. The staff receives signals by the AI while the machines run. It allows them to tweak the machine on the fly.  Now, not only the cost of quality control is lowered, the batch’s value is being improved while it is operating.

Advantages

✓ Easy to setup and adapt without
the need for experts

✓ More accurate, decreasing false positives

✓ Capable of improving as it runs

 

If a picture says more than a thousand words, we can not even count how many words a video is worth.


Watch our short case video here →

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