Machine learning in engineering

Engineering teams face mounting pressure to innovate faster while managing increasingly complex simulations and manufacturing processes. Traditional approaches to finite-element modeling, process optimization, and result validation consume valuable time and resources.

As model complexity grows and design iterations multiply, the need for smarter, faster tools becomes critical. Incorporating machine learning into CAE and CAD workflows is relatively new, but there's significant potential to make a big difference in the way you work.

The solution

Machine learning automates time-consuming engineering tasks and helps you make smarter decisions faster.

Accelerate model building, optimize manufacturing processes, improve simulation accuracy, and explore more design options without running full solvers.

By training models on your expertise and preferences, you can incorporate real-world requirements directly into your workflows, whether designing crash-resistant structures, optimizing aerodynamic performance, or selecting manufacturing processes.

What you can achieve:

• Accelerate finite-element model building and reduce setup time
• Optimize manufacturing processes with intelligent pattern recognition
• Improve simulation accuracy with physics-informed neural networks
• Explore more design options without running full solvers
• Incorporate expert knowledge and preferences into optimization
• Discover hidden patterns in your design libraries and data

Download the fact sheet to unlock the power of machine learning in your engineering workflow.