Auto-generation of paper patterns for children’s jeans

Abstract

This study aimed to address these limitations by employing a systematic approach. Initially, body measurements of 115 children were meticulously recorded and subjected to statistical analysis. Subsequently, a children’s jeans paper pattern was chosen, and a predictive model for pattern sizing was developed using BP neural networks. Additionally, a parametric mathematical model was constructed by integrating the design principles of the paper pattern. Using the Visual-LISP programming language on the Auto-CAD 2020 edition platform, an editing process was performed to create a children’s jeans automatic drawing program. The predicted pattern size data for children’s jeans were then imported into the DCL dialog box of Auto-CAD, enabling the automatic generation of paper patterns. To evaluate the effectiveness of the approach, the generated garment paper patterns were imported into the CLO-3D virtual fitting software.