Solid Model Modification Feature Selection
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Solution Overview
Problem
Current computer-aided design (CAD) systems face inefficiencies in modifying solid models, particularly in history-less systems where design intent is difficult to maintain and requires manual selection of features, leading to cognitive and physical processing overhead and error recovery challenges.
Innovation Solution
A system that allows direct selection of modification features on a solid model using user input, suggesting additional selection features based on modification intent and verifying them visually, thereby simplifying the modification process and reducing error recovery needs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual selection of features is required in history-less systems, then flexibility about change is maintained, but cognitive and physical processing overhead increases and error recovery becomes challenging
Solution Approach 1:
The system performs automatic feature selection itself based on the modification type and model context, eliminating the need for manual selection by the user. The computer automatically identifies and selects relevant features for modification while maintaining flexibility to adapt to different change scenarios.
Solution Approach 2:
The system changes the parameter of selection automation from manual to automatic based on the modification type. By analyzing the context and modification intent, the system dynamically adjusts which features are selected, reducing cognitive overhead while maintaining adaptability to different change scenarios.
2Adaptability or versatility
If design intent is captured at time of edit in history-less systems, then modification flexibility is maintained, but the process becomes cumbersome particularly with very large models
Solution Approach 1:
The system performs preliminary automatic feature selection based on the modification type before the user commits to the change. By pre-identifying relevant features using context analysis and machine learning, the system eliminates the time-consuming manual selection process while maintaining modification flexibility.
Solution Approach 2:
The system uses feedback from the modification context and model structure to automatically determine which features should be selected. This feedback mechanism allows the system to learn from previous selections and improve its automatic feature identification, reducing time consumption while maintaining adaptability.
3Measurement precision
If selection options are set before selecting geometry, then selection precision can be improved, but the complexity of planning ahead and error recovery increases
Solution Approach 1:
Instead of requiring users to set selection options before selecting geometry, the system inverts the process by automatically determining the appropriate selection options based on the modification type and context. This inversion maintains selection precision while eliminating the complexity of planning ahead and error recovery.
Solution Approach 2:
The system performs self-service by automatically configuring selection parameters and identifying relevant features without requiring user input about selection options. This self-configuration maintains precision while simplifying the overall process by eliminating the need for users to understand and set multiple selection parameters.
Data Source
AI summary
A system, method, and computer program for selecting modification features on a solid model that is manipulated in a computer having software instructions, comprising: a computer system, wherein the computer system includes a memory, a processor, a user input device, and a display device; a computer generated geometric model stored in the memory in the memory of the computer system; and wherein the computer system selects a modification feature directly on a solid model using a computer peripheral input that communicates a modification intent from a user; suggests a plurality of additional selection features to include with the modification feature; verifies that the included plurality of additional selection features conforms to the modification intent by a visual highlighting; modifies the solid model according to the modification intent that results in a modified solid model and modified visual display information; and displays the modified solid model using the modified visual display information to the user; and appropriate means and computer-readable instructions.