- Engineering Workflow Automation
- Design Space Exploration
Understanding the behavior of your engineering simulation models is the first important step in setting up a deterministic or robust optimization project. Using Design of Experiments (DOE) early in the process, you can boost your productivity by planning your engineering simulations to deliver a maximum of relevant insights at minimum simulation cost
But when it comes to picking the right DOE strategy, things may become more complicated. Should I use a standard Min – Max approach, or should I choose a random strategy? Should I privilege space-filling techniques, at the risk of missing out on any non-linearities that may exist?
Optimus now offers a smart and fully automated approach that will make the best use of your simulation budget. The new Optimus Adaptive DOE algorithm will learn from the already available data points, and iteratively add extra data samples in design space regions that really matter. This will not just save you a lot of time, but will get you the best information that you can possibly get for your simulation budget.