Model-Based Systems Engineering : Mechanical Product Design

Model-Based Systems Engineering (MBSE) for Mechanical Product Design: From Requirements to Digital Twin

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.

Requirements
- Bachelor’s degree (or equivalent knowledge) in mechanical engineering, mechatronics, or a related field.
- Familiarity with CAD tools and basic engineering simulations (FEA/CFD).
- Understanding of engineering design processes and requirement management.
- No prior MBSE experience is required as concepts are introduced progressively from fundamentals to advanced applications

Description
Thispostgraduate-level online courseprovides acomprehensive, industry-ready introduction to Model-Based Systems Engineering (MBSE)specifically formechanical product design, simulation integration, and lifecycle management.

You will learnhow to transition from document-heavy, disconnected processes to integrated, model-centric engineering workflows. MBSE serves as asingle source of truththat unifiesCAD design, FEA/CFD simulation data, system requirements, and verification activities. This shift enablesfaster design iterations, higher product quality, and improved traceabilityacross engineering teams.

Key skills and outcomes include:

Simulation-driven MBSE- integratingFinite Element Analysis (FEA),Computational Fluid Dynamics (CFD), andMultibody Dynamics (MBD)directly into system models for continuous verification.

Digital twin development- creating living, evolving models connected toreal-time IoT sensor datafor predictive maintenance and operational optimization.

Industry 4.0 integration- connecting MBSE tosmart factories, cloud collaboration, and interoperability standardsfor 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- embeddingcontrol logic, sensor fusion, and safety constraintsdirectly into the engineering model.

Throughout the course, you will gainhands-on conceptual knowledgeof 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 masterdata-driven mechanical engineeringat a level required byIndustry 4.0 and beyond.

By the end of this course, you will be able to:

Apply MBSE methods tocomplex mechanical systemsfrom concept to deployment.

Build and maintaindigital twinsthroughout the product lifecycle.

Usereal-time IoT feedbackto drive continuous design improvement.

EmployAI-assisted designandgenerative algorithmsto create innovative solutions rapidly.

This course is designed formechanical engineers, systems engineers, product designers, and engineering managersaiming to upgrade their skills for thenext generation of model-driven engineering. Whether you’re working inaerospace, automotive, robotics, or industrial equipment, the principles and workflows you’ll learn here will future-proof your engineering capabilities.

Who this course is for:
- Mechanical engineers seeking to upgrade their skills to Industry 4.0 standards.
- Systems engineers integrating mechanical domains into multi-disciplinary MBSE frameworks.
- R&D engineers and product designers aiming to adopt model-based approaches for faster and higher-quality product development.
- Engineering managers who want to implement digital workflows for product lifecycle efficiency.
- Postgraduate students and researchers exploring advanced mechanical system design and simulation integration.
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