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Currently the most commonly used approach to find new chemical formulations and processing parameters is the use of classical Design of Experiments (DoE) software often in combination with statisticians, data scientists or DoE experts. DoE software is often complicated and requires expert knowledge in statistics. This means researchers have to book slots with the limited number of available DoE experts which leads to bottlenecks in the R&D process of many industrial companies.
xT SAAM automates this process by combining classical DoE methods with novel AI algorithms. This allows domain experts and laboratory personnel to run experiments without the need of DoE experts in a fast and efficient manner. Compared to other techniques xT SAAM finds satisfactory results with less samples required, which additionally reduces R&D time and cost.
Pilot projects with our partner Evonik Industries show strong results in the field of mixture design. In synthetic tests against other state of the art AI algorithms we could show superior behavior, especially for high dimensional problems.
Quality issues and production anomalies are often hard to analyze and mitigate, as often only very limited data sets are available. As a result, it is frequently a cost- and time-intensive endeavor.
xT SAAM supports your engineers and researchers by analyzing and developing models based on production data. This simplifies the adjustment of production parameter thresholds.
xT SAAM reduces the time required to investigate and mitigate production anomalies from months to minutes by developing explainable regression and classification models.
Connect xT SAAM directly to your MES system, database or machine using our integrated JSON API. This enables automated development and execution of anomaly mitigation strategies.
