This post briefly introduces SE Methodology.
SE METHODOLOGY CONSIDERATIONS
1. Model-Based System Engineering, MBSE
Model-Based Systems Engineering (MBSE) offers many advantages over traditional document-based approaches. Document-based approaches manage a variety of information about a system in documents, which are often difficult to synchronize and maintain, and whose quality is difficult to assess in terms of accuracy, completeness, and consistency. On the other hand, MBSE enhances your ability to capture, analyze, share, and manage the information that defines a system’s specifications, helping you respond effectively to increased complexity and design changes.
The advantages of MBSE include:
- Improve communication between development stakeholders: Includes project managers, system engineers, hardware and software developers, testers, etc.
- Managing System Complexity: Complexity can be managed by allowing the system to be viewed and understood from multiple perspectives.
- Improved product quality: Provides a precise and clear model of your system so you can evaluate its consistency, accuracy, and completeness.
- Reduce development cycle time: Strengthen technology-based control, enable rapid impact analysis, improve specification and design reuse, provide insight into early design decisions, and enable early detection of potential defects.
- Risk Reduction: Reduce potential risks by identifying requirements and design issues early.
- Enhancing knowledge capture and reusability: Capturing information in a standardized way reduces duplication of information, which also helps teach and learn the fundamentals of systems engineering.
These advantages are supported by quantitative and qualitative data through many papers and presentations from industry, showing that MBSE is a methodology that can better meet the modern needs of systems development.
2. Agile Systems Engineering
Agile systems engineering is a principles-based approach to designing, building, maintaining, and evolving systems in changing environments and under uncertain knowledge conditions. This methodology is especially useful when requirements are constantly changing due to factors such as insufficient initial knowledge, discovery of new knowledge during development, and continuous evolution of the target operating environment. The functional capabilities of a system must continue to evolve as the environment evolves even after initial deployment, and to this end, agile systems engineering uses strategies to develop and apply knowledge in a timely manner.
Agile approaches produce usable or verifiable work results through iterative or evolutionary development, which promotes feedback for real-time learning and application. As software plays an increasingly important role in most systems, agile software development methodologies provide a suitable approach to support the rapid discovery and deployment of knowledge. Additionally, this software approach provides patterns that can be applied to other fields of systems engineering, taking into account the unique differences in each field (e.g. external dependencies, production techniques, development cycle time constraints, development support tools, etc.). It’s possible.
In this way, agile systems engineering contrasts with traditional sequential life cycle approaches and occupies various positions on the life cycle spectrum depending on the degree of attention to and responsiveness to knowledge and the dynamics of the environment. This can be evaluated along a continuum of life cycle approaches, including both traditional and extreme forms of agile methods.
3. Lean Systems Engineering
Lean Systems Engineering (LSE) is a methodology to increase the efficiency of systems engineering (SE) and is based on Toyota’s ‘just-in-time production’ philosophy. This philosophy aims to efficiently produce quality products by eliminating all waste, inconsistencies and unreasonable demands. LSE applies these principles to SE to reduce project waste, provide maximum value to customers, and achieve the best results throughout the life cycle of the system.
According to a study by the U.S. Government Accountability Office (GAO) and NASA, many government projects go over budget and schedule due to problems such as politicization, inadequate coordination, unstable requirements, quality problems, and management frustration. This is because of various forms of waste. A Lean Advancement Initiative (LAI) study conducted at MIT shows that on average, 88% of total work time is wasted on government projects.
With the motto of ‘doing the right job right the first time’, Lian SE increases the quality of SE rather than reducing it, and builds a waste-free workflow by granting higher responsibility and authority. and strengthen mission assurance. It aims to create value without waste in the value creation process in accordance with the Lian Principles. Lian thinking has been successfully applied in a variety of fields, including manufacturing, healthcare, public administration, supply chain management, and product development. This approach pursues the synergy of SE and Lian thinking to provide optimal value throughout the life cycle for technologically complex systems.
4. Product Line Engineering (PLE)
Product Line Engineering (PLE) is a strategic approach to efficiently develop families of similar systems. This approach provides the models, tools, and methods needed to comprehensively design a variety of systems that vary depending on product characteristics and functions.
Key elements of feature-based product line engineering:
- Capability Catalog: Provides a formal model that defines the differences between members of a system family, providing a common language and single authoritative source of truth for variation across the engineering organization.
- Function Specification: Specifies the functions of each system selected from the function catalog.
- Shared asset superset: Contains engineering assets that support the creation, design, implementation, deployment, and operation of a family of systems, and can be included, omitted, created, or converted based on the features selected for each system instance. Includes fluctuation points.
- PLE Factory Configurator: Apply the functional specifications for each system to determine the content of each variation point in the shared asset superset.
- Product Asset Instances: Contains only shared asset content appropriate for specific systems in each system family.
These PLE factories significantly improve efficiency by automating tasks that were previously handled individually, and maintain consistency by performing variation management and configuration management across the entire PLE factory rather than individual systems. PLE results in improvements in a variety of engineering metrics, including lowering system complexity, reducing engineering time, cost, and effort, increasing portfolio scalability, and improving system quality.
Therefore, function-based PLE requires the organizational change and commitment of engineering and business leadership to transform an organization’s engineering approach, while providing a strong return on investment (ROI) to justify this change. This allows engineers to spend more time on high-value, innovative work, advancing overall business and system goals.
If you are interested in other articles about ASEP PREP Series, please refer to the links below!
[ASEP-Prep] #1. What is System LIFE CYCLE?
[ASEP-Prep] #2. Agreement and Enabling Processes
[ASEP-Prep] #3. Technical Management Processes
[ASEP-Prep] #4. Technical Processes – Concept and System Definition
[ASEP-Prep] #5. Technical Processes – System Realization, Deploy and Use