3D CAD Mesh Merging Through AI Feature Alignment
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Solution Overview
Problem
Traditional methods for combining multiple 3-D computer-aided design (CAD) files are time-consuming, inefficient, and require significant expertise, often leading to errors and resource wastage.
Innovation Solution
An AI-driven script that converts CAD files into standardized mesh objects, segments key features, aligns and merges them using geometric transformations, and performs integrity checks to create a seamless, watertight mesh object.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional manual methods are used to combine 3-D CAD files, then the process can be completed with basic software tools, but the process becomes time-consuming and requires significant expertise
Solution Approach 1:
The patent replaces manual mechanical operations in CAD software with an automated AI-based system. The AI script automatically performs feature extraction, alignment calculations, mesh merging, and integrity checks, eliminating the need for manual manipulation while significantly improving merging speed and reducing operational complexity.
Solution Approach 2:
The system enables self-service automation where the AI-driven script independently completes the entire merging process from feature extraction to final mesh validation. The script autonomously handles alignment calculations, merges mesh objects, performs integrity checks, and generates output files without requiring user intervention or expertise in CAD operations.
2Productivity
If manual manipulation methods are used, then basic CAD software can be utilized, but computing resources are wasted and processing efficiency decreases
Solution Approach 1:
The patent extracts only the essential geometric features from each CAD file using AI-based feature detection, rather than processing entire mesh objects. This selective extraction of key features (edges, vertices, critical surfaces) reduces the data volume requiring processing, improving efficiency while minimizing computing resource consumption during the merging operation.
Solution Approach 2:
The system segments the merging process into distinct automated stages: feature extraction, alignment calculation, mesh merging, and integrity checking. Each stage processes only necessary data elements, avoiding redundant computations and optimizing computing resource utilization throughout the workflow.
3Manufacturing precision
If automated AI-based merging is implemented, then productivity and accuracy are improved, but the system complexity increases
Solution Approach 1:
The patent introduces an intermediary AI-driven script that bridges the gap between simple CAD file input and complex merging operations. The script acts as a mediator that automatically handles feature extraction, alignment transformations, mesh merging, and validation, delivering high precision results while shielding users from system complexity through a simple command-line interface.
Solution Approach 2:
The system performs preliminary actions by pre-processing CAD files to extract and store key geometric features before the actual merging operation. This preliminary feature extraction and categorization enables accurate alignment and merging while reducing the complexity of real-time processing during the main merging operation.
4Reliability
If traditional merging methods are used, then the process can be completed with standard tools, but errors and design defects are more likely to occur
Solution Approach 1:
The patent implements feedback mechanisms through automated integrity checks that validate the merged mesh object for structural soundness, watertightness, and feature alignment accuracy. The AI system analyzes the result and provides feedback on potential defects, enabling automatic correction or alerting users to issues that would otherwise go undetected in manual processes.
Data Source
AI summary
Two or more files that each encapsulate a three dimensional (3-D), computer-aided design (CAD) of a different object are received, and each of the representations further include a mesh of objects. After the two or more files are received, key features within each of the files are extracted and then isolated in order to enable targeted operations to be applied to the extracted key features. The now-isolated key features from each of the files are then positioned and aligned with the isolated key features of another of the files. By merging the positioned and aligned features, a mesh object can be generated that is based on at least two of the files. The newly generated mesh object can then be provided to a consuming application or process. Related apparatus, systems, techniques and articles are also described.