Modeling and simulation enable you to try out new ideas and perform fast, repeatable tests. Also, you can automate key steps, like reporting, coding, and verification to eliminate manual steps and reduce human errors.
The models provide you with traceability from requirements development through system architecture, design, simulation, implementation, and testing.
You can use the models as digital twins to perform predictive maintenance, detect faults in real time, and further refine and optimize the system once it is in operation.
Start using Model-Based Design with MATLAB® and Simulink® to shorten iteration cycles and reduce your development time by 50% or more.
Using MATLAB and Simulink for
“With MathWorks tools for Model-Based Design, we have one integrated tool chain from the beginning of development to the end. We have clear traceability of requirements, and our software is more maintainable because it is implemented as a model from which we automatically generate code.”Thomas Ehl, Continental
Model-Based Design is for:
Simulation and formal methods promote continuous testing throughout the development process, enabling you to adhere to agile development practices and shorten software development cycles.
Find errors with automation before hardware-software integration to achieve higher quality.
Apply modeling and analysis to system requirements and system architecture.
Author architecture models directly, import them from other tools, or populate them from the architectural elements of Simulink designs. Use a single environment for descriptive architecture models that bridge into detailed implementation models.
Create models of your physical assets containing important performance parameters to maintain and optimize your current systems.
Connect digital twins to assets that produce continuous streams of operational and performance data sent through a cloud-based infrastructure.
DevOps represents a continuous, iterative path between development and operation, which enables you to deliver software updates in the field.
The key is to use your models and data to create quality products and services for your customers throughout the lifecycle.
Getting Started with Model-Based Design
When introducing new design tools and process changes, there is a risk of slowing down development. Successful teams have mitigated this risk by introducing Model-Based Design in stages, starting with a single project or algorithm, identifying an achievable return on investment (ROI), and building on initial modeling success.
- Airnamics Develops Unmanned Aerial System for Close-Range Filming with Model-Based Design
- ENGEL Speeds Development of Injection Molding Machine Controllers
- Enabling Small Development Teams with Model-Based Design: Q&A with Airnamics
- Mondragon University Students Build Practical Engineering Skills Through Project-Based Learning
- Simulink for Simulation and Model‑Based Design
- System Modeling and Simulation
- Agile System Development with Model-Based Design
- Model-Based Systems Engineering
- What Is a Digital Twin? 3 Things You Need to Know
- MATLAB and Simulink for Verification, Validation, and Test
- MATLAB and Simulink for Embedded Code Generation