Parametric 3D Shape Data Classification via Distance-Based Dimensional Relationships
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Solution Overview
Problem
Current 3D shape design processes are inefficient due to the lack of appropriate classification and derivation of dimensional relationships between shape data portions, particularly for shapes with curves or holes, leading to difficulties in parametric modeling and design intent interpretation.
Innovation Solution
A specifying program that calculates a first distance between a shape data center point and a straight line on the same plane, adds this distance to the dimensional information, and specifies the dimensional relationship between different shape data portions, enabling the construction of a parametric model reflecting design intent.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If past 3D shape data is used for diversion design without appropriate classification, then design efficiency is improved by reusing existing data, but the quality of design intent interpretation deteriorates due to insufficient classification and large number of similar shapes
Solution Approach 1:
The patent segments 3D shape data into multiple portions and classifies each portion independently to establish dimensional relationships. By dividing the shape data into distinguishable portions and analyzing their dimensional relationships separately, the system achieves both efficient reuse of past data and accurate interpretation of design intent through systematic classification.
Solution Approach 2:
The patent derives dimensional relationships between portions by analyzing parameters such as distances from center points to straight lines. By changing and analyzing multiple dimensional parameters systematically, the system classifies shape data appropriately while maintaining design efficiency through parametric modeling.
2Loss of time
If dimensional relationships between shape portions are not derived, then processing time is reduced by avoiding complex analysis, but the ability to perform parametric design deteriorates due to insufficient classification
Solution Approach 1:
The patent performs preliminary classification and derivation of dimensional relationships between shape portions before actual design work. By pre-establishing the dimensional framework and relationships in past 3D shape data, the system enables rapid parametric design later without repeating complex analysis, thus reducing processing time while maintaining parametric design capability.
3Measurement precision
If manual classification of 3D shape data is performed to improve design intent interpretation, then measurement precision is improved, but productivity deteriorates due to large number of manual operations required
Solution Approach 1:
The patent replaces manual classification operations with automated computational methods that calculate dimensional relationships between shape portions. By substituting mechanical manual operations with automated algorithms that derive dimensional relationships systematically, the system achieves accurate design intent interpretation without the productivity loss associated with manual classification of large datasets.
Data Source
AI summary
A computer-readable recording medium stores a specifying program for causing a computer to execute a process. The process includes: calculating a first distance between a center point of each shape data and a straight line on a same plane as the center point, for a specific portion of which the center point is defined, from among a plurality of portions included in a shape indicated by each shape data classified into the same group; adding the calculated first distance to dimensional information of the specific portion in each shape data; and specifying a dimensional relationship between different portions of the shape data in the group, based on the dimensional information for each portion of each shape data in the group.