Accelerating Innovation with Simulation-Based Design & Generative AI
8 July 2026 | 3:00 PM - 4:30 PM
Online via Zoom
Overview
As engineering systems grow in complexity, traditional development methods often fall short, leading to costly late-stage errors and integration delays. Model-Based Design (MBD) solves these challenges by using a centralized digital model at the center of your development workflow.
This webinar offers a practical, end-to-end look at MBD. We will walk through the entire lifecycle of a system—from modeling physical hardware (Plant Design) and creating the logic to govern it (Control Design), to leveraging cutting-edge Artificial Intelligence (AI) to optimize and accelerate the entire process. Attendees will see firsthand how moving from mental models to executable simulation models drastically cuts development time and improves system reliability.
Highlights
|
Virtual Prototyping (Plant Design) |
Discover how to build high-fidelity mathematical models of physical systems (mechanical, electrical, or thermal) before any physical hardware is built. |
| Closed-Loop Control Logic | Watch a live demonstration of designing, tuning, and testing control algorithms against the virtual plant to ensure stability and performance. |
| Agentic AI | See how an autonomous AI agent uses the MATLAB® MCP Core Server to open a live Simulink® workspace, programmatically layout block architectures from a requirements list, and run thousands of parallel simulations. |
| Early Verification & Validation | See how simulation allows you to test "what-if" scenarios and extreme fault conditions safely and efficiently on the desktop. |
Speaker
Yoworex To Tiu
Application Engineer
TechSource Systems Group
Yoworex Tiu is an Electronics engineer with over four years of experience in product applications, specializing in analog devices such as switches and multiplexers. Skilled LTspice simulation, microcontroller, circuit and evaluation board development, with hands-on experience supporting a large portfolio of products and contributing to new product releases. Known for improving workflows through Python-based automation and streamlining customer support processes.
Experienced in managing multiple projects in fast-paced environments, collaborating with cross-functional teams, and delivering high-quality technical documentation. Combines strong problem-solving skills with a focus on efficiency, accuracy, and customer satisfaction.
Key Takeaways
• A Clear MBD Blueprint: A solid understanding of the "V-model" development cycle and how Simulink connects requirements to implementation.
• Hardware-Free Testing Skills: The knowledge of de-risking projects by validating control code using a virtual plant.
• Autonomous Iteration Strategies: How to offload repetitive verification cycles, documentation formatting, and parametric sweeps to an AI agent while keeping final engineering decisions securely in human hands.
• Boosted Productivity: Insights into how automated code generation from Simulink models eliminates manual coding errors.
Who Should Attend
• Control Systems Engineers looking to design and optimize algorithms more efficiently.
• Systems & Plant Engineers focused on high-fidelity physical modeling and simulation.
• Engineering Managers & R&D Leaders aiming to reduce time-to-market and improve team collaboration.