AI Design Specification Generation From Natural Language Inputs

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Solution Overview

Problem

Existing product design processes are inefficient and time-consuming, requiring manual drafting and extensive research to develop design specifications for parts and structures, especially for users lacking expertise in geometry, dimensions, and material properties.

Innovation Solution

A method utilizing a computer system that automatically generates a design specification by accessing a textual descriptor, extracting language signals, selecting output characteristics, linking input parameters to model variables, and compiling functions into a design specification, aided by machine learning and virtual models to streamline the design process.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If manual drafting and extensive research are used to develop design specifications, then the design specification can be developed with expert knowledge, but the process becomes inefficient and time-consuming

Engineering Contradiction:

Improvedesign specification accuracyVSAvoiddesign development time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system enables self-service by automatically generating design specifications through AI that extracts requirements from natural language descriptions and autonomously performs parameter selection, constraint identification, and specification compilation without requiring manual expert intervention

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces the mechanical system of manual expert analysis and drafting with an AI-based automated system that uses natural language processing, machine learning, and knowledge graphs to generate design specifications, eliminating the need for physical manual work while maintaining or improving accuracy

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Adaptability or versatility

If manual drafting processes are used, then design specifications can be customized for complex geometries and materials, but the process requires extensive manual effort

Engineering Contradiction:

Improvedesign specification customizationVSAvoiddesign workflow efficiency

Core Design Contradiction:

Adaptability or versatilityVSProductivity

Solution Approach 1:

The system handles parameter changes by dynamically adjusting design parameters based on AI analysis of the input description, automatically modifying geometry, materials, and constraints to match the specified requirements without manual intervention

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The patent implements universality by creating a multi-functional AI system that can handle various types of design problems (different geometries, materials, and constraints) through a single automated platform, replacing multiple specialized manual processes with one versatile system

Inventive Principle:

Principle #6Universality (Multi-functionality)

3Reliability

If expert knowledge is required for geometry, dimensions, and material properties, then the design specification can be technically accurate, but users lacking expertise cannot effectively use the process

Engineering Contradiction:

Improvetechnical accuracyVSAvoiduser accessibility

Core Design Contradiction:

ReliabilityVSEase of operation

Solution Approach 1:

The AI system acts as an intermediary between the user's natural language description and the technical design specification, translating layman's terms into accurate engineering parameters without requiring the user to have expert knowledge of geometry, materials, or dimensions

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The system performs self-service by automatically conducting the expert analysis that would otherwise be required, with the AI autonomously selecting appropriate parameters, validating constraints, and ensuring technical accuracy without human expert intervention

Inventive Principle:

Principle #25Self-service

4Productivity

If automated systems are used to generate design specifications, then the design workflow is accelerated, but the system complexity increases

Engineering Contradiction:

Improvedesign workflow speedVSAvoidsystem complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The patent applies segmentation by dividing the automated design specification generation into distinct functional modules: natural language processing module, requirement extraction module, parameter selection module, constraint identification module, and specification compilation module, making the complex system manageable and maintainable

Inventive Principle:

Principle #1Segmentation

Data Source

PatentUS20260030395A1Method for automatically generating a design specification for a part, assembly, or structure

Publication Date: 2026.01.29 GENERATIVE VISION LTD

AI summary

One variation of a method includes: receiving a descriptor of a design problem; selecting a set of output characteristics based on a set of language signals extracted from the descriptor; selecting a set of functions relating a set of input parameters to the set of output characteristics; accessing a virtual model representing a design solution and defining a set of model variables; linking a subset of input parameters to a subset of model variables analogous to the subset of input parameters; in response to the set of model variables omitting a model variable analogous to a first input parameter in the set of input parameters, prompting a user to update the virtual model to include a first model variable analogous to the first input parameter; and compiling the set of functions, the set of output characteristics, and the set of input parameters into a design specification.