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Sustainable Sizing.

Kathleen M Robinette1, Daisy Veitch2

  • 1Oklahoma State University, Stillwater kathrobinette@gmail.com.

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|May 28, 2016
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Summary
This summary is machine-generated.

Sustainable sizing practices reduce waste and increase sales by improving product fit. Fit-mapping with real people is effective, while virtual fitting needs improvement with standardized data collection for future success.

Keywords:
anthropometrydesign strategiesfit-mappingsystem designtest and evaluationworkstation

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Area of Science:

  • Apparel design and manufacturing
  • Sustainable business practices
  • Human factors engineering

Background:

  • Sustainable sizing integrates environmental and business benefits by reducing material waste, size variations, and unsold inventory.
  • These practices enhance sales through better market fit and customer satisfaction with improved product accommodation.
  • Current statistical and modeling approaches often result in poor fit, necessitating a review of effective methods.

Purpose of the Study:

  • To review sustainable sizing practices that minimize waste and enhance product fit and sales.
  • To contrast current sizing methodologies with more effective sustainable approaches.
  • To evaluate the efficacy of virtual fitting versus real-world methods.

Main Methods:

  • Review of sustainable sizing strategies, focusing on waste reduction and sales enhancement.
  • Analysis of fit-mapping and case-based methods using real people and products.
  • Contrast of traditional statistical/modeling practices with proposed sustainable methods.
  • Evaluation of virtual fitting technologies and their limitations.

Main Results:

  • Fit-mapping and case studies with real individuals and products yield superior design outcomes, ensuring fit for purpose and optimal comfort.
  • Virtual fitting simulations with digital models are currently ineffective for accurate fit prediction.
  • Sustainable sizing methods demonstrably reduce material usage and unsold stock, leading to cost savings.

Conclusions:

  • Fit-mapping with real-world data provides effective product design and optimized sizing.
  • Standardized data collection for fit-mapping is crucial for developing a global fit-map database.
  • Improving virtual fitting requires integrating fit-mapping data for enhanced predictive accuracy.