3D CAD Model Simplification via Feature Merging and Reference Mapping
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Solution Overview
Problem
Complex 3D CAD models with many features lead to substantial processing overhead and lengthy rebuilding times, especially when included in assemblies or drawings, due to the need to manage and store extensive incremental operations and references.
Innovation Solution
A method to simplify 3D models by creating a new feature to replace multiple features, maintaining necessary references through unique identifiers and mappings, thereby reducing data storage and preventing operation failures, while allowing for the removal of extraneous features and proprietary aspects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple features are stored in a history-based CAD model to maintain design flexibility and reference integrity, then the model can support powerful editing capabilities and automatic rebuilding, but the model size increases significantly and processing performance deteriorates
Solution Approach 1:
The patent extracts and removes selected features from the history-based CAD model while preserving the essential geometry. The feature removal process deletes specific features from the model history, reducing model complexity and size while maintaining the core design through remaining features and geometry.
Solution Approach 2:
The patent discards unnecessary feature history data that is no longer needed for design edits, while recovering and preserving the essential geometric information through direct geometry modification. This allows the model to maintain its functional form without the burden of extensive feature history.
2Speed
If all incremental operations are stored to enable fast rollback and rebuild operations, then editing performance is improved, but memory usage and processing overhead increase
Solution Approach 1:
The patent extracts and removes unnecessary incremental operation data from the model history, keeping only the essential operations needed for basic edits. This reduction in stored operations decreases memory usage and processing overhead while maintaining sufficient edit capability for common operations.
Solution Approach 2:
The patent applies partial action by selectively removing only certain incremental operations rather than all of them. The most critical operations are retained to maintain rebuild capability, while less essential operations are discarded to reduce data storage requirements.
3Adaptability or versatility
If the complete feature history is maintained to allow full design editing, then design flexibility is preserved, but proprietary information may be exposed when sharing models
Solution Approach 1:
The patent extracts and removes features containing proprietary or sensitive design information from the model history. This selective feature removal hides proprietary aspects while preserving the essential geometry and functionality of the model for sharing purposes.
Solution Approach 2:
The patent applies local quality by differentiating between features that should be hidden (proprietary information) and features that should be preserved (essential geometry). The simplification process selectively modifies specific portions of the model history while leaving other portions intact, creating a differentiated information structure.
4Productivity
If features are removed to reduce model complexity, then processing performance improves, but reference integrity may be compromised causing operation failures
Solution Approach 1:
The patent introduces an intermediary process that systematically manages reference updates when features are removed. This intermediary mechanism tracks and adjusts all references to removed features, ensuring that operation references remain valid and reference integrity is maintained throughout the simplification process.
Solution Approach 2:
The patent implements feedback mechanisms that monitor reference integrity during the feature removal process. When features are simplified or removed, the system automatically detects and corrects any broken references, providing continuous feedback to maintain operational reliability throughout the simplification process.
Data Source
AI summary
A computer-implemented method constructs a three-dimensional (3D) model, deletes data defining two or more features of the 3D model, and creates a new feature to replace the two or more features. Each of the two or more features has a set of faces, and a reduced amount of data is associated with the new feature with respect to the amount of data defining the two or more features. The method maps unique identifiers, enabling references to be retained and preventing a failure of an operation that uses the reference.