Course Information
Course Overview
Model-Based Systems Engineering (MBSE) for Mechanical Product Design: From Requirements to Digital Twin
This postgraduate-level online course provides a comprehensive, industry-ready introduction to Model-Based Systems Engineering (MBSE) specifically for mechanical product design, simulation integration, and lifecycle management.
You will learn how to transition from document-heavy, disconnected processes to integrated, model-centric engineering workflows. MBSE serves as a single source of truth that unifies CAD design, FEA/CFD simulation data, system requirements, and verification activities. This shift enables faster design iterations, higher product quality, and improved traceability across engineering teams.
Key skills and outcomes include:
Simulation-driven MBSE - integrating Finite Element Analysis (FEA), Computational Fluid Dynamics (CFD), and Multibody Dynamics (MBD) directly into system models for continuous verification.
Digital twin development - creating living, evolving models connected to real-time IoT sensor data for predictive maintenance and operational optimization.
Industry 4.0 integration - connecting MBSE to smart factories, cloud collaboration, and interoperability standards for seamless manufacturing alignment.
AI-augmented MBSE & generative design - leveraging machine learning and optimization algorithms to accelerate innovation and reduce time-to-market.
Autonomous mechanical systems design - embedding control logic, sensor fusion, and safety constraints directly into the engineering model.
Throughout the course, you will gain hands-on conceptual knowledge of how MBSE integrates with digital engineering tools to create robust, high-performance mechanical products. By connecting design, simulation, manufacturing, and operational data into a single digital ecosystem, you will master data-driven mechanical engineering at a level required by Industry 4.0 and beyond.
By the end of this course, you will be able to:
Apply MBSE methods to complex mechanical systems from concept to deployment.
Build and maintain digital twins throughout the product lifecycle.
Use real-time IoT feedback to drive continuous design improvement.
Employ AI-assisted design and generative algorithms to create innovative solutions rapidly.
This course is designed for mechanical engineers, systems engineers, product designers, and engineering managers aiming to upgrade their skills for the next generation of model-driven engineering. Whether you’re working in aerospace, automotive, robotics, or industrial equipment, the principles and workflows you’ll learn here will future-proof your engineering capabilities.
Course Content
- 12 section(s)
- 59 lecture(s)
- Section 1 Introduction
- Section 2 Module 1 : Foundations of MBSE in Mechanical Product Design
- Section 3 Module 2 :Core Principles & Terminology
- Section 4 Module 3 : MBSE Process Workflow for Mechanical Product Development
- Section 5 Module 4 : SysML and MBSE Toolchains for Mechanical Engineers
- Section 6 Module 5 : Requirements Engineering in MBSE for Mechanical Systems
- Section 7 Module 6: Mechanical Design Case Studies, Pumps, Engines, Robotics Examples
- Section 8 Module 7 : Integration with Simulation & Analysis: FEA, CFD, MBD
- Section 9 Digital Twin Development via MBSE
- Section 10 Module 9 : Industry 4.0 & MBSE: IoT Feedback Loops for Mechanical Systems
- Section 11 Module 10: Current & Future Developments: AI, Generative Design & Autonomy
- Section 12 The MBSE Skills you now have
What You’ll Learn
- Understand the core principles of Model-Based Systems Engineering (MBSE) in a mechanical engineering context., Apply MBSE to integrate CAD, simulation, and system-level requirements into a unified engineering model., Establish secure, compliant, and data-driven feedback loops for continuous mechanical product improvement., Integrate MBSE with Industry 4.0 workflows, IoT data streams, and predictive analytics.
Skills covered in this course
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