AI-Assisted System Model Generation for Low-Expertise MBSE
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Solution Overview
Problem
Existing systems require advanced specialized knowledge and numerous man-hours to create system models, particularly in model-based systems engineering (MBSE), and struggle with generating models across multiple regions and submodels.
Innovation Solution
A design support system that analyzes user input, specifies appropriate templates from a database, extracts necessary information using AI, and generates system models, reducing user load and aligning with user intentions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a system model is created using traditional methods with template models and parameters, then the model creation process is systematic, but it requires advanced specialized knowledge and numerous man-hours
Solution Approach 1:
The system enables self-service model generation by automatically analyzing user input and generating system models without requiring specialized knowledge. The natural language processing and AI technologies allow the system to serve itself in understanding requirements and producing models, eliminating the need for expert intervention while maintaining model quality
Solution Approach 2:
The patent replaces manual mechanical processes of model creation with automated information processing systems. Natural language processing, AI analysis, and automated template selection substitute for the manual work of specialists, dramatically reducing man-hours while preserving model accuracy through intelligent algorithms
2Reliability
If a system model is created using traditional methods with template models and parameters, then structured modeling is achieved, but advanced specialized knowledge is required
Solution Approach 1:
The system introduces an intermediary layer of natural language processing and AI analysis between the user and the complex modeling system. This intermediary translates simple user input into structured model specifications, shielding users from the complexity of specialized knowledge while maintaining high-quality model structure through intelligent mediation
Solution Approach 2:
The patent substitutes manual expert analysis with automated AI-based information extraction and analysis systems. These systems perform the cognitive tasks previously requiring specialized knowledge, making the modeling process accessible to users without expert background while preserving structural quality
3Ease of manufacture
If template models are used for creating system models, then model creation is standardized, but it is difficult to generate models across multiple regions and submodels
Solution Approach 1:
The system achieves universality by creating a unified model generation platform that handles multiple regions and submodels through a single integrated process. The AI-based analysis and template selection mechanisms work across different model types and regions, providing standardized yet adaptable model creation that covers diverse system modeling needs without requiring separate specialized processes
Data Source
AI summary
An input information analysis unit that analyzes input information of a user regarding a system model, a model candidate specifying unit that specifies a system model to be generated from system model information in which a plurality of types of templates of the system models is registered, based on an analysis result of the input information, an information extraction unit that extracts necessary information used to generate the system model from a database that stores information regarding design, based on the analysis result of the input information, and a system model generation unit that generates a system model according to the input information, using the extracted necessary information and the template of the system model to be generated are included.