Knorr-Bremse’s AI Agent Engineering Workflow for FEM and fatigue analysis
Knorr-Bremse is a global leader in braking and safety systems for rail and commercial vehicles - an industry where precision, consistency, and speed directly impact product quality and customer confidence.
Knorr-Bremse’s engineering teams were running Finite Element Method (FEM) and Fatigue Analysis Tool simulations on highly complex components such as crankshafts. A process that requires manual preparation: defeaturing, surface detection, meshing, and preparing models for specialist simulations.
Even for experienced engineers, these tasks were time-consuming. As a forward-thinking organization with the highest safety and quality standards, Knorr Bremse wants engineering teams to focus on what moves the business forward.
AI Meets FEM and fatigue analysis
Knorr-Bremse chose Synera’s AI Agent platform for engineering to automate the entire pre-processing workflow for crankshaft FEM and fatigue analysis. After connecting their engineering software tools to the platform and creating workflows, the team deployed a multi-agent AI system to perform the analysis. Engineers simply uploaded their STEP and configuration files, then prompted the AI agents to run the required analysis sequence.
The new agentic engineering workflow followed three steps for the engineers:
- Upload STEP and config files to Synera
- Prompt the multi-agent system to perform the analysis
- Let the agents prepare the model: defeaturing, detecting surfaces, and generating the mesh automatically. Afterwards engineers export the analysis-ready results.
By deploying AI agents in their existing software ecosystem, Knorr-Bremse’s engineers kept full control while eliminating repetitive manual tasks.
This approach allowed engineers to shift their focus to higher-value work: evaluating results, driving innovation, and improving product performance.
Synera integrates our software ecosystem into a unified, AI-ready platform where engineers can automate a wide range of tasks to spend more time on moving the business forward.
Dr. Zoltán Gyurkó, Team Leader - Bálint Farkas, Simulation Engineer - Zsombor Csuvár, Software Development Engineer
AI Engineering Agents Deliver Consistency, Quality, and Speed
Knorr-Bremse moved from manual model preparation to a fully automated, AI-powered workflow that improved the quality of their work.
✓ Higher product quality
Automated model preparation removed the risk of human error during defeaturing, surface detection, and meshing — directly leading to more reliable FEM and fatigue analysis inputs.
✓ Increased customer happiness
Higher product quality translated into improved customer satisfaction — a key metric highlighted in the document.
The AI Effect: A Before-and-After Look at FEM/FEMFAT Model Preparation
Before:
- Manual model prep
- Issues with meshes and surfaces across projects
- Engineers tied up in repetitive tasks
After:
- Fully automated model preparation via Synera AI agents
- Electrically consistent, error-free analysis inputs
- Engineers focusing on strategic engineering and product innovation
Knorr-Bremse’s transformation shows what’s possible when AI agents are embedded directly into engineering workflows. By automating complex FEM and fatigue analysis preparation, engineering teams gain speed, consistency, and the freedom to focus on innovation.
If you’re looking to automate repetitive engineering tasks and unlock a new level of productivity, explore how AI Agents for Engineering can transform your workflows.
