Spline Model Morphing Using Inspection Data and Warp Functions
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Solution Overview
Problem
Current CAD modeling techniques require extensive manual effort and conversion processes to handle geometric inconsistencies, leading to productivity losses and frustration due to the inability to directly modify CAD models based on inspection data, resulting in loss of metadata and lack of direct relationship between physical parts and design models.
Innovation Solution
The method involves determining a warp function based on the differences between an as-designed watertight spline model and an as-inspected model, using measurement points and metadata to create a continuous function that characterizes discrepancies, allowing for direct modification of the CAD model and maintaining semantic PMI data throughout the design-through-inspection lifecycle.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual repair and conversion processes are used to handle geometric inconsistencies, then model compatibility is improved, but productivity deteriorates due to extensive manual effort and time consumption
Solution Approach 1:
The system performs preliminary actions by automatically detecting geometric inconsistencies and generating repair operations before manual intervention is needed. The warp function is computed in advance to guide subsequent model conversions, eliminating the need for extensive manual repair work during the workflow.
Solution Approach 2:
The patent introduces an intermediary computational layer that automatically mediates between the as-designed watertight spline model and the as-inspected model. This intermediary system computes warp functions and generates intermediate representations that bridge geometric inconsistencies without requiring manual conversion operations.
2Reliability
If intermediate geometric modeling representations are used for conversion, then model format compatibility is improved, but loss of metadata and semantic PMI data occurs
Solution Approach 1:
The system extracts and preserves semantic PMI data and metadata separately from the geometric conversion process. By taking out this information from the intermediate representation step, the patent prevents data loss during format conversions while still achieving model compatibility through the warp function-based approach.
Solution Approach 2:
The patent creates a digital twin copy of the as-inspected model that maintains the same semantic PMI data and metadata as the original as-designed model. This copying approach allows multiple format conversions without losing information, as each conversion operates on a faithful replica that preserves all original data.
3Manufacturing precision
If extensive manual repair operations are performed, then geometric accuracy is improved, but time consumption and productivity loss increase
Solution Approach 1:
The system implements feedback by automatically comparing the as-designed watertight spline model with the as-inspected model, detecting geometric inconsistencies, and generating corrective warp functions. This closed-loop feedback mechanism achieves geometric accuracy automatically without requiring manual inspection and repair operations.
Solution Approach 2:
The patent replaces manual mechanical repair operations with an automated computational system that computes warp functions and generates repair operations algorithmically. This substitution eliminates the need for manual intervention while maintaining geometric accuracy through mathematical optimization.
4Adaptability or versatility
If conventional CAD modeling techniques are used, then design flexibility is maintained, but the ability to directly modify models based on inspection data is lost
Solution Approach 1:
The system introduces dynamics by making the CAD model modifiable through computed warp functions that can be applied based on inspection data. The model transitions from a static, immutable design representation to a dynamic structure that can be automatically updated with feedback from inspection processes, maintaining design flexibility while enabling direct modification.
Data Source
AI summary
Determining a warp function between two watertight spline models. A first watertight spline model of a first object and a set of points and associated metadata from a second object are received. A second watertight spline model of the second object is constructed based on the set of points, the metadata, and the first watertight spline model. A warp function is determined based on a difference between the first watertight spline model and the second watertight spline model. The warp function is a continuous function approximating differences between the first object and the second object. The warp function is stored in a non-transitory computer-readable memory medium.