AI masterclass 2026: takeaways on turning physical test data into competitive advantage

AI master class 2026: takeaways on turning physical test data into competitive advantage

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.

System Simulation for humanoid robots – Turning complexity into competitive advantage with Simcenter Amesim

This blog introduces System Simulation for designing Humanoid Robots virtually with digital twins in Simcenter Amesim. It’s mechatronics with multiphysics to virtually size and assess the performances of Humanoid Robots with simulations executed in few seconds.

Close-up of a CNC milling tool actively cutting a metal workpiece, with metal shavings and coolant fluid spraying outward during high-speed machining

The artisan’s ear in the digital age: Reimagining tool life with AI and Executable Digital Twins

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Why do we need rotor dynamics analysis? Modern turbomachinery, from jet engines to industrial compressors, runs at high speeds and…

E-drivetrain measurements to insights

A 4-step approach to transform multiphysics e-drivetrain measurements into meaningful initial engineering insights

Electric drivetrain programs generate massive amounts of multiphysics data — yet many teams still struggle to turn it into trusted engineering decisions. This article presents a proven 4‑step approach to transform raw electrical, mechanical, and vibration measurements into validated, correlated, and repeatable insights, using a unified Simcenter Testlab workflow from measurement to decision.

The inaugural AI master class 2026: Unlock competitive advantage with your physical test data

Unlock the power of your engineering test data in this three‑day AI master class. Build practical AI workflows, improve NVH and durability processes, and boost innovation through hands‑on training. Read this blog to learn more and register to accelerate your AI‑driven engineering future.

3 essential questions answered: How to combine NVH, power or even high voltage zone data

🚀 Introduction As the electric vehicle (EV) revolution gains momentum, testing engineers face a dual challenge: ensuring mechanical integrity while…

Tetra Pak Machinery and Packages global view

Tetra Pak – Making food safe and available, everywhere and protect what’s good: food, people and the planet

Tetra Pak uses Simcenter to undergo digital transformation, leading the way in food packaging, availability and safety. Leading with safe…

At SAE Noise and Vibration Conference and Exhibition 2025: Learn to solve modern NVH testing challenges with Simcenter

Visit the Siemens booth at the SAE Noise and Vibration Conference and Exhibition in Grand Rapids, Michigan USA from May 12-15. Don’t miss this opportunity to learn how to redefine your NVH testing landscape.