Intelligent mechanical design method and system based on learning-generation AI-AD

Through the AI-AD intelligent mechanical design method and system based on learning-creation, using natural language interaction and LLM multi-agent architecture, the shortcomings of intelligent CAD systems in design innovation and intelligent reasoning are solved, and automated design and high-precision model generation are realized, which are suitable for complex and non-standard design needs.

CN119647013AInactive Publication Date: 2025-03-18ZHEJIANG UNIV OF SCI & TECH
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Patent Information

Application Number
CN202411727529.3
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-11-28
Publication Date
2025-03-18
Estimated Expiration
Not applicable · inactive patent

AI Technical Summary

Technical Problem

The existing intelligent CAD system has shortcomings in design innovation and intelligent reasoning, and cannot effectively support non-standard design and innovative design needs, and there are deviations in handling complex geometric features and high-precision manufacturing.

Method used

Using learning-creation-based AI-AD intelligent mechanical design methods and systems, using a multi-agent underlying architecture of all natural language interaction and LLM, we generate a 3D model that meets user requirements through continuous human-computer interaction and context-based reasoning.

Benefits of technology

It realizes automated design, synchronous modeling process of generating VBA codes, embedded dialogue interfaces and cloud design data traceability, reducing design complexity, improving accuracy and automation level, and is suitable for complex parts and high-precision manufacturing needs.

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Abstract

The invention discloses an AI-AD intelligent machine design method and system based on a learning-generation mode. The method comprises the following steps: S1, enabling an AI-AD intelligent mechanical design system to understand design knowledge at first; s2, compiling a workflow with low codes; s3, compiling a Prompt strategy of the design Agent and a called knowledge base; s4, repeating the steps S1 to S3, and compiling various agents needing to complete various specific design functions; s5, according to the designed various agents, a multi-agent self-organizing framework is utilized, and product creation type design is completed; and S6, according to the generated design result, generating a VBA file and storing the VBA file in the cloud. And S7, the SW establishes a conversation with the agent through a back-end API of the agent, timely reads a VBA code of the cloud for modeling, and outputs a model. According to the invention, a system structure of knowledge processing, cloud data storage, SolidWorks-based secondary development modeling and a human-computer interface module is constructed, Agents are enabled to learn at first, then design is created, and a 3D model meeting user requirements is generated, so that the current situation that knowledge engineering has extremely high requirements for practitioners' admission threshold can be reduced.
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