Variational Modeling Dependency Rules for Removal Features
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Solution Overview
Problem
Current CAD and PLM systems face challenges in correctly handling variational edits involving removal features, particularly in identifying and managing dependencies between features, which can lead to incorrect geometric or topological results when features become interacting during editing processes.
Innovation Solution
The system detects interactions between features, applies dependency rules to correctly sequence the removal and re-creation of removal features, rolling back the model if necessary to ensure accurate editing and solving, and re-applying the variational solve with the correct dependency order.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the system performs variational edits on geometric models with removal features, then the model can be modified and edited, but incorrect dependencies between features may lead to geometric or topological errors
Solution Approach 1:
The system performs preliminary interaction detection between features before executing the variational edit. By detecting whether features interact with each other in advance and establishing dependency relationships beforehand, the system ensures that removal features are processed in the correct sequence, preventing geometric and topological errors while maintaining model editing flexibility
Solution Approach 2:
The system implements a feedback mechanism where the interaction detection process continuously monitors feature relationships during model editing. When dependencies are detected, the system adjusts the editing sequence accordingly and performs rolling back if necessary, ensuring that the final model maintains geometric accuracy while allowing versatile edits
2Manufacturing precision
If the system detects interactions between features and applies dependency rules, then feature removal sequencing is improved, but the editing process becomes more complex
Solution Approach 1:
The system segments the feature removal process into distinct phases: interaction detection, dependency analysis, sequencing determination, and execution. By dividing the complex editing process into manageable segments with clear decision points, the system achieves precise feature removal sequencing while keeping the overall process organized and controllable
Solution Approach 2:
The interaction detection and dependency rule application are performed preliminarily before the actual feature removal. This preliminary analysis establishes the removal sequence in advance, allowing the system to execute features in the correct order without requiring complex real-time decision-making during the removal process itself
3Manufacturing precision
If the system rolls back the model to handle discovered interactions, then accurate geometric models are produced, but additional computational steps are required
Solution Approach 1:
The system performs preliminary interaction detection before executing the full variational edit sequence. By identifying feature interactions in advance and establishing dependency relationships beforehand, the system can determine the correct removal sequence without requiring rolling back, thereby maintaining geometric accuracy while reducing computational overhead
Solution Approach 2:
When interactions are detected during the editing process, the system skips unnecessary rolling back steps by having already established the correct dependency relationships through preliminary detection. This allows the system to rush through the remaining steps with the known correct sequence, minimizing additional computational time while ensuring accuracy
Data Source
AI summary
A system, method, and computer readable medium. A method includes receiving a geometric model in an initial state including at least a first feature and a second feature, at least one of the first and second features being a removal feature. The method includes detecting an interaction between the first and second features, and applying a dependency rule to the first feature and the second feature. The method includes performing a variational edit process including removing the first feature and the second feature according to the dependency rule. The method includes solving and recreating the edited model.