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This project uses an existing product as an example to investigate sizing development tailored for the Dutch market, leveraging a database of 554 body scans. The methodology involves a suite of tools:

  • Clo3D for garment analysis, to create virtual, three-dimensional clothing models to understand fit and drape better.

  • CAESAR database information is exported into Excel, providing a comprehensive set of body measurements for analysis.

  • Excel for creating ellipse graphs, which are then employed to perform sizing calculations.

  • Paraview for visualizing the average body type, helping generate the typical appearance of certain sizes.

  • Clo3D is used again to overlay and examine individual 3D body scans within the specified size range to ensure accurate and realistic sizing.

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The product chosen: 

Bauerfeind shoulder braces

Utilize clo3D for product simulation and find out critical measurements.

An Ellipse Graph was created using shoulder breadth and arm circumference data to develop a size intended to fit 99% of the Dutch population.

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Size developement

extreme values within one size range is merged into a average size 3D model. 

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average body for each size

Test the product fit on individuals (3D scans of real people from the database).

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  1. Evaluations Summary: Utilized the CAESAR database for selecting five diverse 3D body scans, refined with MeshLab, and integrated with CLO3D skeletons for simulation. Key limitations included default fabric settings and assumptions about material uniformity and properties.

  2. Simulation Setup: Adjustments in fabric properties and mesh settings were made to enhance realism, though constrained by computational capacity.

  3. Evaluation Criteria: The CLO 3D evaluation focused on visualizer observation, fit mapping, and pressure mapping, revealing important insights about garment fit and stress levels.

  4. Mannequin Results: Visual, fit, and stress mapping evaluations showed generally positive results across five mannequins, with minor discrepancies and high-pressure areas noted.

  5. Additional Evaluations: Other factors like garment stress weren't fully explored but indicated effective movement restriction.

  6. Discussion and Conclusion: The study highlights the variability in sizing and the impact of anatomical differences. It underscores the potential of 3D scanning and Clo3D in improving garment design but notes the limitations in material data accuracy and the need for more comprehensive evaluations.

Citation:

  1. Clo3D. (2023). Particle distance setting . Clo Support. https://support.clo3d.com/hc/en-us/articles/115000414447-Particle-Distance-Setting- 

  2. Kuzmichev, V. E., & Cheng, Z. (2020). Sizing and fit for pressure garments. Anthropometry, Apparel Sizing and Design, 331–370. https://doi.org/10.1016/b978-0-08-102604-5.00013-5 

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