Design of Experiment
STOCHOS runs on your local server
By using STOCHOS for the experiments in your domain, you can assure to always extract all the information the experiment data provides. A task that in many cases is almost impossible for humans.
Use the models generated by STOCHOS to predict new designs or formulations, find errors in your processes or monitor your production.
The automatic noise detection and the overall probabilistic nature of the models assure an astonishing reliability, combining the computational power of AI algorithms and the holistic viewpoint of domain experts.
Minimize your trials
Simplifying Experiments with Smart Technology
We experience a paradigm shift in data acquisition as our machine learning algorithm optimizes each experiment, ensuring that the amount of information gained is maximized.
Compared to common colorimetry software, we can use AI to optimize your formulations not only for color accuracy, but also for all other properties such as gloss, opacity, viscosity and production costs. We can also achieve good results in the area of metallic coatings and color values using multi-angle measuring devices.
STOCHOS has substantiated its effectiveness in the coating industry, yielding tangible results for prominent players in the market. With the capability to automatically identify your input/output relations, our software requires only your domain knowledge, eliminating the need for any expert AI knowledge.
Example:
A fully automatic development within 5 adaptation cycles of a coating consisting of a total of 17 parameters:
-Raw material types like binder, additives, dispersing agents…
-Concentrations
-Process parameters like spray settings, speed mixer…
Keep your data where it belongs
STOCHOS runs on your local server
We understand that in the coating industry, your formulations and recipes represent crucial intellectual property. With us, there’s no need to upload your sensitive data outside your company. Additionally, thanks to our probabilistic approach, computation times, even on a desktop, are remarkably short.
Multi-fidelity Modeling
Predict dried properties based on liquid coating
With multi-fidelity modeling optimization simulation times can be extremely reduced as accurate models can be generated within a fractional amount of time. It is even suitable for simulation calibration (combination of simulation and real experimental data), especially if precise simulation calibration is not possible for any reason.
If a simulation or an experiment is too complex or expensive, STOCHOS ML-driven optimization is a good alternative to achieve very good results –even for high-dimensional problems!
Explore in low-fidelity e.g., liquid color
Exploid in high-fidelity e.g., dried color
A New Era in Machine Learning
PI Probaligence
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