Webinars

Physical testing is essential but often time-consuming and expensive. Engineers are frequently left with small, noisy datasets and high-stakes decisions. In other cases, modern engineering teams collect vast amounts of test data, but often lack the tools to extract full value from it. Modern design of experiments, data sampling, and predictive machine learning models combined with analysis techniques from uncertainty quantification can enable more efficient test planning and accurate predictive modeling from sparse, noisy test data, leading to more confident decision making and actionable insights. Join us for this webinar in which SmartUQ principal application engineer, Gavin Jones, will discuss SmartUQ’s tools for collecting, modeling, and analyzing test data. The unique strengths and capabilities of SmartUQ’s tools will be highlighted along with a software demonstration and examples from customer use cases.