Fishbone Model for System Engineering Design Verification
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Solution Overview
Problem
Traditional systems engineering methods are cumbersome and error-prone due to their text-based nature, making it difficult to manage complex engineering systems, and existing model-based systems engineering methods require significant expertise and are complex to implement, leading to inefficiencies in system design and verification.
Innovation Solution
A fishbone model-based system engineering method that acquires and represents system-level static and dynamic information as composite structure diagrams and function point diagrams, allowing for consistency adjustments between static and dynamic software function modules to ensure integrity and consistency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional text-based systems engineering methods are used, then the system can be designed and documented, but the process becomes time-consuming, laborious, and error-prone when managing complex engineering systems
Solution Approach 1:
The patent replaces text-based manual documentation with model-based automated generation. Models serve as the new foundation, automatically generating documentation, requirements, and design artifacts, thereby eliminating the time-consuming and error-prone manual text processing while ensuring data consistency through the single source of truth principle.
Solution Approach 2:
The patent creates multiple views and artifacts by copying from a unified model rather than manually creating separate documents. This allows consistent replication of system information across different documentation types without the time and error costs of manual text-based documentation.
2Ease of operation
If model-based systems engineering methods are used, then communication and knowledge acquisition are improved, but the syntax complexity and expertise requirements increase significantly
Solution Approach 1:
The patent segments the complex model-based systems engineering methodology into a simplified fishbone diagram approach. This breaks down the system into causal relationships that can be easily visualized and understood, reducing syntax complexity while maintaining the benefits of model-based engineering for communication and knowledge acquisition.
Solution Approach 2:
Instead of starting with complex formal models and generating diagrams from them, the patent inverts the approach by starting with simple fishbone diagrams and automatically generating the underlying models. This reverses the traditional flow, making the entry point much simpler while still achieving model-based engineering benefits.
3Reliability
If existing MBSE methods with complex syntax are used, then comprehensive system modeling is achieved, but the modeling process becomes confusing and chaotic for engineers
Solution Approach 1:
The patent introduces fishbone diagrams as an intermediary between simple visual understanding and complex formal models. These diagrams serve as a mediator that captures causal relationships in an intuitive format, which then automatically translates into comprehensive models, eliminating the confusion of direct complex syntax while maintaining system reliability.
Solution Approach 2:
The patent performs preliminary analysis and model construction through the fishbone diagram phase before generating the final comprehensive models. This preliminary action simplifies the complex modeling process by first establishing causal relationships in an intuitive format, making the subsequent model generation straightforward and non-chaotic.
Data Source
AI summary
A method for designing and verifying system engineering based on fishbone model is provided. System-level static information, system-task-level static information, and system-task-level dynamic data flow are acquired. Based on fishbone diagram, the system-level static information is represented as a system static composite structure diagram, and the system-task-level static information is represented as a system task composite structure diagram. Based on the fishbone diagram, the system-task-level dynamic data flow is represented as a system function point dynamic data flow diagram. Based on the system task composite structure diagram and the system function point dynamic data flow diagram, a static set and a dynamic set of software function modules of the system are established, and consistency adjustment is performed between the software function modules in the static set and the dynamic set. A designing and verifying system is further provided.


