What is MBSE (Model-Based Systems Engineering)?
MBSE (model-based systems engineering) is a methodology that uses models to support the entire lifecycle of a system, from conception and design to verification, validation, and even decommissioning.
Unlike traditional systems engineering, which relies on document-based processes, MBSE uses digital modeling and simulation to represent system components and their interactions in a visual and interactive manner.
This approach is particularly beneficial for complex systems, as it enhances clarity, reduces errors, and improves communication among engineering teams and stakeholders.
The role of MBSE in digital engineering
MBSE provides a structured framework for managing complex systems. It allows engineers to create a digital representation of a system, enabling them to simulate and test different scenarios before actual construction. This capability helps identify potential issues early in the design process, saving time and resources.
Using MBSE, organizations can consolidate system knowledge across various engineering disciplines into standardized models. These models serve as the primary artifacts in systems engineering tasks throughout the system’s lifecycle. This consolidation facilitates better decision-making by providing a single source of truth, reducing developmental risks, and ensuring consistency across all project phases.
What are the benefits of MBSE?
Improve system quality
Give engineers the ability to evaluate system performance under various conditions using simulations. This helps optimize designs for better reliability and performance.
Save costs
Reduce the need for costly rework and late-stage changes by enabling early detection of design issues through simulations. This efficiency translates into significant cost savings.
Enhance requirements management
Reduce the risks of missing or misunderstanding requirements by linking them directly to system components and ensuring that they’re accurately captured and traced throughout the engineering process.
Improve risk management
Use models to simulate and analyze potential risks, enabling engineers to evaluate different risk mitigation strategies early in the development process. This proactive approach helps minimize the impact of risks on system development.
Ensure digital continuity
Provide a centralized model that serves as a single source of truth, enhancing digital continuity and traceability across the system’s lifecycle. This reduces miscommunications and development risks by ensuring all team members have access to consistent information.
Support digital twin
Gain insights that might be impractical to obtain through physical testing. Creating virtual representations of physical systems enables testing and optimization in a risk-free digital environment.
Automation and reusability
Enable automation in documentation generation and support the reuse of models for similar systems. This accelerates system development and reduces costs associated with creating new models from scratch.
What's the best way to get started with MBSE in your organization?
Keep reading to discover our recommended approach to MBSE, or reach out to us for a free consultation today.
Bring in engineers, project managers, and clients to gather comprehensive system objectives and requirements.
Document requirements clearly and ensure they are traceable throughout the system’s lifecycle.
Compare different MBSE tools based on criteria such as compatibility with existing systems, scalability, ease of use, and support for specific modeling languages (e.g., SysML).
Conduct pilot testing with selected tools to assess their effectiveness in real-world scenarios.
Ensure that all team members understand how to use MBSE tools effectively and are familiar with best practices.
Encourage continuous learning through workshops, webinars, and access to online resources to keep the team updated on the latest MBSE techniques and tool updates.
Establish governance processes for model creation, validation, and maintenance. This includes defining roles and responsibilities for model management and setting standards for model quality.
Implement version control systems to manage changes to models over time. This ensures that models remain consistent and up-to-date throughout the project lifecycle.
Integrate MBSE processes with existing engineering workflows to ensure seamless collaboration across different teams and departments.
Adopt an iterative approach to model development, allowing for regular feedback from stakeholders. This helps in refining models based on real-world insights and evolving project requirements.
Continuously monitor the performance of MBSE implementations to identify areas for improvement and ensure alignment with project goals.
Need help with MBSE model-based systems engineering?
Johannes Storvik and team are on-hand to provide tailored guidance and support with a deep knowledge of the full Dassault Systèmes portfolio. Reach out for a free consultation today.
Essential software for MBSE
CATIA Magic
For creating, collaborating, and managing complex system specifications.
Dymola
For modeling and simulation of complex, multi-engineering systems.
For end-to-end PLM (product lifecycle management) and collaborative innovation.
View our extensive range of software solutions