Siemens Digital Industries Software Blogs

What is new in Simcenter 3D 2606 Our Simcenter solvers, combined with Simcenter 3D, offer engineers a comprehensive post-processing experience....

Humans and computers working hand in hand to complete tasks and solve problems has, for decades, seemed like little more...

From raw test data to AI-driven decisions in just three days—here’s what happened at the AI Master class in Leuven, where engineers got hands-on with AI. Over three intensive days, participants progressed from AI fundamentals to building fully integrated workflows. They learned how to prepare AI-ready data, automate validation and feature extraction, and train models for real engineering use cases, including road-noise prediction and manufacturing quality classification. By combining physical testing expertise with scalable AI workflows, the master class demonstrated how organizations can accelerate decision-making, improve model reliability, and unlock the full value of their test data—today and in the future.

To celebrate the beginning of summer, we take a behind-the-scenes look at how a water slide works using Simcenter Flomaster.

NX for Manufacturing 2606 is here, bringing a set of powerful enhancements to NX Manufacturing and NX X Manufacturing that...

Software is a great enabler across industries and disciplines, but for manufacturing and production especially it needs to be grounded...

Siemens is for its leadership in AI manufacturing, leveraging Insights Hub Production Copilot and Copilot Studio. These solutions utilize agentic AI to transform industrial data, enabling faster insights and enhanced decision-making in production environments.

The new Simcenter FLOEFD 2606 CFD software release includes Smart Die for modeling complex power distributions on a IC package die, enhanced Smart PCB FEM mesh thermal analysis option, easier to use component libraries, and headless EDA Bridge operation for advanced automation of electronics thermal analysis and optimization workflows.

The future of humanoid robots depends on combining AI-driven continuous learning and powerful semiconductor architectures.