Webtraining – Accurate Machine Learning for Engineering Simulation

Accurate, Comprehensive Machine Learning Software for Engineering Simulation and Digital Twin Applications

As part of a growing shift toward digital engineering, simulation and digital twins are widely used by many industries including aerospace, defense, automotive, industrial machinery, and semiconductor. As the Department of Defense’s Digital Engineering Strategy guide states, the benefits of digital engineering include addressing the challenges of complexity and uncertainty, which leads to benefits such as better-informed decision making, more confidence in designs, and more efficient engineering processes. Quantified Margins and Uncertainties and tools that support such a framework are important to the sort of risk informed decision making needed to realize the full benefits of digital engineering. In order to capture the benefits of digital engineering, digital transformation initiatives have become important to companies and organizations in all industries. Digital transformation includes increased use of simulation and digital twins. Across the lifecycle digital twins have benefits to improved efficiency, product quality, reliability, and the optimization of maintenance activities. To help address their digital engineering and transformation needs, Fortune 100 and 500 companies across many industries including aerospace, defense, automotive, semiconductor, energy, and medical device are currently using SmartUQ.

Machine learning webtraining

During this webtraining an Application Engineer will present customer simulation and digital twin use cases from a variety of industries including aerospace, defense, and automotive. This will be followed by a brief training showing how to use ML tools for solving the sorts of engineering problems presented in the first half of the workshop.

Machine learning Agenda

The webtraining will be 90 minutes in total, with 60 minutes of presentation. The remaining 30 minutes will be for audience Q&A both during and at the conclusion of the presentation. Attendees are encouraged to come prepared with any of their own questions on the use of Artificial Intelligence and ML.