Engineering Schematic Editing via Natural Language and Ontology Queries
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Solution Overview
Problem
Existing computer-aided design tools for engineering schematics require extensive user training and manual effort to translate high-level design concepts into detailed schematics, lacking the ability to understand natural language instructions and maintain schematics efficiently.
Innovation Solution
A system and method using natural language processing and knowledge graphs to interpret user inputs, generate or modify engineering schematics, ensuring compliance with industry standards by identifying components, actions, and attributes, and rendering visual representations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If conventional computer-aided design tools are used to create engineering schematics, then the schematics can be generated with standard components and libraries, but the process requires extensive user training and manual effort
Solution Approach 1:
The patent replaces manual mechanical interaction with design tools (drag-and-drop interfaces, menu navigation) with natural language processing. Users speak or type natural language descriptions of desired schematics, and the system automatically generates the visual representations, eliminating the need for users to learn complex software interfaces while maintaining schematic creation capabilities
Solution Approach 2:
The system performs automatic schematic generation and validation without requiring user intervention for manual component placement or configuration. The AI model independently interprets natural language input, selects appropriate components from libraries, arranges them according to engineering standards, and validates the schematic, making the system self-sufficient in the creation process
2Manufacturing precision
If manual schematic drawing is performed to ensure clarity and correctness, then the schematics can be iteratively improved, but the process is time-intensive and repetitive
Solution Approach 1:
The system performs preliminary actions by automatically generating complete schematics from natural language descriptions before any manual review is needed. The AI model pre-configures all components, connections, and attributes according to engineering standards, providing a ready-to-review schematic that eliminates repetitive manual drawing while maintaining accuracy through automated validation rules
Solution Approach 2:
The system incorporates automated validation that provides immediate feedback on schematic correctness by checking against engineering standards and constraints. This feedback mechanism ensures accuracy without requiring multiple manual iteration cycles, as the system automatically identifies and corrects errors in the generated schematics
3Reliability
If existing schematic maintenance is performed to ensure complete understanding of the system, then the schematics can be updated correctly, but the process is as challenging as authoring from scratch
Solution Approach 1:
The patent introduces an AI-based intermediary layer between the user and the schematic maintenance process. Users provide natural language descriptions of desired changes, and the AI model interprets these descriptions, automatically updates the schematic while maintaining consistency with the overall system design, and validates the changes. This intermediary eliminates the need for users to completely understand the existing schematic structure while ensuring reliable maintenance
4Ease of operation
If natural language processing is implemented to interpret user intent, then the interaction becomes more intuitive, but the system complexity increases
Solution Approach 1:
The patent implements a multi-functional AI processing system that handles multiple tasks within a single integrated architecture: natural language interpretation, component selection from libraries, schematic layout generation, validation against engineering standards, and visual representation rendering. This universal system performs all these functions through one cohesive AI model, making the increased complexity manageable while providing intuitive natural language interaction
Data Source
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AI summary
Disclosed is a method (100) for generating and modifying engineering schematics. The method comprises receiving a natural language input via a user interface, the input containing a user intent to perform operations on an engineering schematic. The method generates a structured representation of the input using a language model, identifying components, actions, and attributes. Knowledge graph queries are generated based on this representation, compatible with a standardized ontology. These queries are executed to retrieve component, connection, and attribute data from the knowledge graph. A system representation of the schematic is generated using the retrieved data and specified actions. The method then renders a visual representation of the engineering schematic based on this system representation and outputs it via the user interface. This approach allows for intuitive schematic modification using natural language processing and knowledge graph technologies.