Model-Based System Engineering-07Oct21-1

Overview

Today's engineering systems are getting more and more complex with frequently added complex requirements to shorten time of delivery to minimizing the field issues. Engineers use Model-Based Systems Engineering (MBSE) to manage system complexity, improve communication and produce optimized system performance. Successful MBSE requires the synthesis of stakeholder requirements into architecture models to create intuitive system descriptions.

Are you happy with your current tool choices for modelling system architecture?

MATLAB, Simulink, System Composer and Simulink Requirements together provide a platform to create a single descriptive architecture model that seamlessly bridge into detailed implementation models. The connected environment ensures items across the architecture and design worlds stay in sync. Systems engineers can establish a digital thread to navigate between system requirements, architecture models, implementation models, and embedded software.

 

Hear Use Cases like how Mercedes-Benz R&D India creates System Architecture using System Composer

 

Highlights include:

  • Capture and manage system requirements enabling impact and coverage analysis.
  • Optimize system architectures by capturing architecture metadata and directly connecting to MATLAB analytics for domain-specific trade studies
  • Create simplifying customized model views to isolate the components of interest for different engineering concerns
  • Validate requirements and verify system architectures using simulation-based tests
  • Translate and refine requirements into architectures with components ready for simulation and implementation using Model-Based Design in Simulink

 

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Hear from Our Model-Based Engineer how MATLAB creates a single environment for creating descriptive architecture models that seamlessly bridge into detailed implementation models.

 

Supamith Sutharojana, Application Engineer Team Lead (Thailand)

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Supamith and his team helps engineers across different industries with various applications like Predictive Failure Detection using Machine Learning, Data Forecasting Analytics, Powertrain Calibration and Testing, Vehicle Analysis and Validation, etc.

He specializes in the areas of Model-Based Design and Auto Code Generation with MATLAB/Simulink. He holds a bachelor’s degree from Chulalongkorn University major in Automotive Engineering. Before joining Ascendas Systems, he was an Engine Software Designer at Toyota Daihatsu Engineering & Manufacturing working in Engine Calibration and Engine software development field.

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