Development of Automated Custom-Made Pants Driven by Body Shape

Abstract

Mass customization and automated custom clothing have been regarded as promising methods for the apparel industry to create well-fitting clothing for customers. However, current off-the-shelf automated custom patternmaking software cannot generate custom clothing with perfect fit since alteration starts from a single graded base pattern regardless of customers' body shape, resulting in an extreme pattern alteration in areas that the system cannot accomplish effectively for some customers. Therefore we developed a set of basic pants patterns optimized for three lower body shape groups, and tested whether improved customization could occur if the alteration process is started from differently shaped block patterns that are suitable for each body figure. The body shape groups were identified using a new data driven method using multiple body measurements (depths, angles, and arcs). The results showed that the new made-to-measure system incorporating body shape information into block patterns can generate custom patterns with better fit.