Virtual sensors?
Virtual sensors are software-based models which can calculate process parameters. To do this, the models are trained using (real) sensor data. First, the training data is analyzed and prepared using state-of-the-art data processing methods. Afterwards, we can expand the training data with our process knowledge, by adding simulated values to the measurements. The resulting model (or virtual sensor) is now able to use inputs from real sensors to calculate the target variable.
Your vision is our vision
Perfect knowledge of your process parameters. All the time. Utilize the power of neural networks combined with process expertise in biotechnology.
How it works
In hybrid modeling, we combine real and simulated data. The simulated data contains our process knowledge, but real data describes complex processes best. We want to bring the best of both worlds together, to achieve robust, high-quality process models.
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Glimpse into the future
With the use of data driven methods, we can achieve models that are able to describe even the most complex processes. This enables closed control loops for virtually every process parameter, leading to better automation and greater stability.
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Smarter, better, faster
Outspeed your competitors by unlocking your data's full potential. Gain knowledge about your process in real-time and focus on the more important aspects of your work.