[Systems Engineering] #8. Additional practical knowledge about MBSE

Continuing from my last post, I will talk a little more about MBSE, especially Additional practical knowledge about MBSE.

Model Based Systems Engineering is a model-driven approach to performing systems engineering processes. In contrast to traditional document-centric approaches, this methodology uses an integrated model for the design, analysis, verification, and management of systems.

The primary purpose of Model Based Systems Engineering is to manage system complexity, improve project efficiency, and reduce errors. Potential benefits include:

  • Improved communication: Shared understanding of the system and integration of different perspectives between the development team and stakeholders.
  • Reduced development risk: More accurate cost estimates through ongoing requirements and design validation.
  • Improved Quality: Complete and clear requirements, strict traceability, and improved design integrity.
  • Improved productivity: Rapid impact analysis of requirements and design changes, reuse of existing models, and automated documentation generation.
  • Use the model throughout the life cycle: Operator training, system diagnostics, and maintenance support.
  • Improved knowledge transfer: Capture existing and legacy designs, access and modify information efficiently.

Model Based Systems Engineering centers on a system model that includes the structure, behavior, properties, requirements, and constraints of the system. This model serves as the overall ‘blueprint’ of the system and serves as the basis for design decisions.

Model Based Systems Engineering utilizes models throughout all stages of the systems engineering process. This applies to the entire life cycle of the system, starting from requirements definition, system design, verification, and operation.
This methodology integrates with a variety of software tools to support system modeling and analysis and is used to predict system performance, identify problems, and evaluate various design alternatives. MBSE plays an important role in simulating and analyzing the behavior of a system before building a real system.

This image is a picture drawn by Dall-e with the keyword Additional practical knowledge about MBSE
This image is a picture drawn by Dall-e with the keyword MBSE (Model Based System Engineering).

So what do you need to know to do Model Based Systems Engineering properly?

Implementing Model Based Systems Engineering requires understanding and proficiency in modeling languages, modeling methods, and modeling tools.

(The content of this section is referenced from Lenny Delligatti’s book SysML Distrilled chapter 1.2 The Three Pillars of MBSE.)

1. Modeling Language: A modeling language is a tool used to easily express and describe complex systems. These languages are different from the natural languages we use in everyday life. That’s because they are specifically created to clearly and accurately represent the structure and operation of a system, its necessary elements, and its constraints.
For example, a modeling language specifies how to represent various elements and the relationships between them. In particular, graphical modeling languages allow these elements to be depicted graphically.
Modeling languages use shapes called diagrams to represent elements and their relationships. This allows engineers to visually represent complex systems and easily communicate with team members.

One of the most popular modeling languages is SysML, or Systems Modeling Language. Learning SysML is an important first step toward model-based systems engineering (MBSE).

2. Modeling Methodology: Modeling methods are an important component of Model-Based Systems Engineering (MBSE), providing a set of guidelines and principles for the process of designing and documenting systems using modeling languages.
This method guides you through the steps necessary to define the requirements of a project and model the structure and behavior of the system. This helps increase project consistency and efficiency. Let’s look at the important aspects of the modeling method:

  • Define the purpose of modeling: The first step in modeling is answering the question ‘Why are we modeling?’ The purpose of modeling can be many, including recording design decisions (Rationale for all design decisions), managing requirements traceability, performing trade studies for alternative configurations, or executing system models and including integration test cases.
  • Determine Modeling Scope: The next step is to determine the scope of the system to be modeled. This involves determining which parts of the system should be modeled, what behavior should be modeled, and how detailed the internal structure and behavior should be decomposed.
  • Selection and adjustment of modeling method: Select an appropriate modeling method according to the purpose and scope of the system and adjust as necessary. There are several modeling methods to choose from that are documented in the literature, including INCOSE’s object-oriented systems engineering method (OOSEM), Weilkiens’ systems modeling (SYSMOD) method, and IBM’s Telelogic Harmony-SE.
  • Application of modeling methods: The selected modeling method must be tailored to the specific requirements of the project, which is essential for the successful execution of the project. By adopting appropriate modeling methods and applying them to projects, teams can build system models consistently and effectively.

3. Modeling Tools: Modeling tools are the third core element of Model Based Systems Engineering. These tools are used to apply modeling languages and methods to real-world projects. These tools are used to create, manage, and analyze system models. They facilitate the visualization, documentation, and verification of complex systems.
They also support project management and cross-team collaboration. Modeling tools are different from simple diagramming tools. Diagramming tools are designed to Whereas modeling tools only provide a visual representation of the Changes are automatically reflected in all related diagrams.

Mastering and integrating all three skills is important for successful implementation of Model Based Systems Engineering. Learning a modeling language is fundamental, after which it is necessary to understand and apply how to use modeling methods and tools effectively.
The return on investment (ROI) that can be achieved through MBSE comes from integrating these three pillars to optimize the design and management of the system. Model Based Systems Engineering can make a significant contribution to managing the complexity of systems engineering, increasing project efficiency, and improving the quality of the final product.

Stakeholders who do not directly implement Model Based Systems Engineering, such as external customers, executives, and internal downstream design and development teams, often have the misconception that MBSE easily simplifies complex engineering tasks and reduces costs. However, MBSE must consider several important points, including:

  1. Need for Hard Work and Discipline: Model Based Systems Engineering does not replace the rigor and hard work required in the process of designing complex systems. Rather, it further emphasizes the in-depth analysis and thorough design work required for project success.
  2. Modeling Complexity: Creating a good model is a difficult task that requires time, effort, and discipline. It is possible to create a bad model or a good model based on a poorly designed system. This means that careful design is required to achieve the appropriate level of breadth, depth, and fidelity to meet the model’s objectives.
  3. Change Management and ROI: Model Based Systems Engineering provides Return on Investment (ROI), especially when changes occur, i.e. when new design decisions are made and stakeholder requirements evolve throughout the system life cycle. . Change is inevitable, and MBSE is an effective tool for managing and adapting to these changes.
  4. Managing stakeholders’ expectations: It is important to realistically manage stakeholders’ expectations during the introduction and implementation of MBSE. This will help you understand the benefits MBSE offers and correct misperceptions.
  5. Initial Investment Required: Effective implementation of MBSModel Based Systems EngineeringE requires an initial investment in processes, methodologies, tools, and training. This provides the foundation for making the design and management of your system more efficient and is an essential step for long-term success.
  6. Integration with document-based approaches: Many existing systems use a document-based approach, and integration with these legacy systems becomes a significant challenge when introducing MBSE. In particular, modeling may only be partially applicable in existing systems.
  7. Alignment of Modeling Approach and Scope: Every project has unique requirements and constraints, so MBSE’s modeling approach and scope must be tailored to the characteristics of the project. This is an essential element for the successful execution of a project.

Successful application of MBSE involves the use of appropriate methodologies and tools, establishing the necessary training and support systems, and tailoring the modeling approach and scope to the specific needs of the project.

This approach significantly improves the efficiency and effectiveness of systems engineering, but it is not an automatic or effortless process. MBSE is a powerful tool for designing and managing complex systems, but its success depends on thorough planning, execution, and ongoing management.

Additionally, the MBSE transition process must be gradual, and interaction and integration with existing document-based systems are important. Especially when dealing with complex legacy systems, a strategy is needed to drive the transition to MBSE while gradually reducing reliance on existing documentation.

This implementation and application goes beyond the simple use of tools and requires an integrated approach and change in mindset throughout the systems engineering process. This transition significantly improves the efficiency and effectiveness of systems engineering and can have a positive impact on the overall quality and performance of the system.

In this post, we discussed Model Based Systems Engineering in more detail.

In my upcoming post, I’m going to talk about three really important questions. First, what is a ‘good model’? Here we will explore the characteristics and importance of a good system model.

Second, what are we trying to achieve by using Model Based Systems Engineering? We will look at what positive changes Model Based Systems Engineering can bring to our work. Lastly, I would like to find out how SysML can help us. It will provide insight into how this language applies to system modeling and why it is important. Through all of this, I think it will be an opportunity to delve deeper into the world of systems engineering.

[Systems Engineering] #1. INTRODUCTION – Navigating Systems Engineering

[Systems Engineering] #2. Definition of System

[Systems Engineering] #3. Understanding Systems Thinking

[Systems Engineering] #4. Useful knowledge of systems thinking

[Systems Engineering] #5. Understanding Systems engineering

[Systems Engineering] #6. Who is Systems Engineer

[Systems Engineering] #7. Understanding MBSE (Model Based Systems Engineering)

[System Engineering] #9. MBSE (Model Based System Engineering) – 3

[System Engineering] #10. SysML (System Modeling Language)

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