Automated Unmoldable Portion Detection in 3D-CAD
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Solution Overview
Problem
Current methods for detecting unmoldable portions in 3D-CAD systems require specialized knowledge and are time-consuming, as engineers must manually confirm the presence of undercuts in molds, which hinders productivity in mass production.
Innovation Solution
An automated system that calculates normal lines from surfaces of a three-dimensional shape to determine if they have a backward component opposite to the mold pull direction, using units such as normal line arithmetic, backward component determination, and unmoldable portion determination to identify unmoldable surfaces, and additional units to assess concave connections and projection surfaces.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual confirmation of undercut presence is performed by engineers, then detection accuracy is maintained, but detection time increases significantly
Solution Approach 1:
The patent replaces the manual mechanical inspection process with an automated computer-based system that calculates normal lines and analyzes their directional components relative to mold pull direction. This substitution maintains detection accuracy while eliminating time consumption associated with manual engineering review.
Solution Approach 2:
The system enables automatic self-detection of unmoldable portions through algorithmic analysis of surface normal lines, allowing the computer system to perform the detection function independently without requiring engineer intervention or specialized knowledge input.
2Measurement precision
If specialized knowledge about mold design is required for undercut detection, then detection accuracy is maintained, but ease of operation deteriorates
Solution Approach 1:
The system encodes specialized mold design knowledge into automated algorithms that automatically analyze normal line directions and identify unmoldable portions. This eliminates the requirement for operators to possess specialized knowledge while maintaining detection accuracy through programmed expert rules.
Solution Approach 2:
The patent replaces the need for human expert judgment with an automated computational system that applies mathematical and geometric analysis to detect unmoldable portions, making the operation accessible to users without specialized mold design training.
3Productivity
If automatic detection of undercut is implemented, then productivity increases, but detection accuracy may deteriorate
Solution Approach 1:
The patent implements automatic detection through computer-based calculation of normal lines and their directional components, replacing manual inspection to enable high-speed automated analysis that maintains accuracy while dramatically improving productivity for mass production applications.
Solution Approach 2:
The system provides automated feedback by calculating and analyzing normal line directions relative to mold pull direction, automatically identifying surfaces with backward components that indicate unmoldable portions, thereby enabling rapid and accurate detection without human intervention.
Data Source
AI summary
An unmoldable portion detection system includes: a normal line arithmetic unit; a backward component determination unit; and an unmoldable portion determination unit, wherein the system further includes one of the following (A) units and (B) units: (A) a concave connection determination unit; and an adjacent unmoldable portion determination unit, and (B) a projection line reach determination unit; and a projection unmoldable portion determination unit.