Garment Size Grid Algorithm for Custom-Like Fit
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Solution Overview
Problem
Current garment sizing systems fail to properly fit a large majority of consumers, as they are based on limited size ranges and rely on consumers to guess their body type, leading to high dissatisfaction and the need for alterations.
Innovation Solution
A novel method for creating a large number of garment sizes based on individual body measurements, using statistical analysis and an algorithm to categorize and prioritize variant measures, resulting in a custom-like fit size grid that can fit nearly 97% of the population.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a limited number of sizes (XS, S, M, L, XL, XXL) are used to minimize manufacturing costs and inventory, then manufacturing efficiency is improved, but fit satisfaction deteriorates as only about 15% of consumers can be properly fitted
Solution Approach 1:
The patent segments the continuous range of body measurements into multiple discrete size categories. Instead of using only 6 traditional sizes, the system creates a comprehensive size grid with numerous sizes by segmenting measurement ranges for chest, waist, hip, and other body parts. This segmentation allows the system to accommodate a much broader population (up to 97%) while maintaining manufacturing efficiency through standardized pattern blocks and automated grading processes.
2Ease of manufacture
If traditional grading processes are used to create sizes from a single pattern, then manufacturing simplicity is improved, but measurement precision deteriorates as the system cannot account for individual body shape variations
Solution Approach 1:
The patent applies parameter changes by systematically varying multiple measurement parameters (chest, waist, hip, sleeve length, etc.) to create different size patterns. The system uses statistical analysis to determine optimal parameter values for each size category based on population data. This approach maintains ease of manufacture through automated computer-based pattern creation while significantly improving manufacturing precision by accounting for actual body measurement variations across different population groups.
3Device complexity
If consumers are required to know their body type and guess their size, then the sizing system complexity is reduced, but ease of operation deteriorates as consumers struggle to select the correct size
Solution Approach 1:
The patent implements self-service by providing consumers with simple measurement tools and guidelines to measure their own body parts (chest, waist, hip, etc.). Instead of requiring consumers to determine their body type or guess their size based on complex categorization systems, the patent enables them to directly measure their dimensions and use these measurements to select the appropriate size from the comprehensive size grid. This approach reduces system complexity from the consumer's perspective while dramatically improving ease of operation.
Data Source
AI summary
Garments are produced from patterns with a size grid that provides custom-like fit for ready-to-wear garments. The patterns are generated from a size chart of groups, sub groups and sub sub groups of anchor measures and priority measures. The size grid for various garments (men, women, children) includes a large number of sizes, anywhere from a few dozen to over two hundred. Given measures of a customer, these measures are screened against the groups, sub groups and sub sub groups to determine a correct size.