Investigating the development of digital patterns for customized apparel

Abstract

Purpose

The paper aims to provide an overview of the area of digital pattern developing for customized apparel.

Design/methodology/approach

The paper outlines several methods of digital pattern developing for customized apparel, and discusses the principles, characters and applications. Digital pattern developing process has two paths. One path develops apparel according to traditional 2D pattern‐making technology. There are three methods: parametric design, traditional grading technique, and pattern generating based on artificial intelligence (AI). Another path develops pattern through surface flattening directly from individual 3D apparel model.

Findings

For parametric method, it can improve greatly the efficiency of pattern design or pattern alteration. However, the development and application of parametric Computer‐Aided‐Design (CAD) systems in apparel industry are difficult, because apparel pattern has fewer laws in graphical structure. For grading technique, it is the most practical method because of its simple theory, with which pattern masters are familiar. But these methods require users with higher experience. Creating expert pattern system based on AI can reduce the experience requirements. Meanwhile, a great deal of experiments should be conducted for each garment with different style to create their knowledge databases. For 3D CAD technology, two methods of surface flattening have been outlined, namely geometry flattening and physical flattening. But many improvements should be done if the 3D CAD systems are applied in apparel mass customization.

Originality/value

The paper provides information of value to the future research on developing a practical made‐to‐measure apparel pattern system.

Citation

Yang, Y., Zhang, W. and Shan, C. (2007), "Investigating the development of digital patterns for customized apparel", International Journal of Clothing Science and Technology, Vol. 19 No. 3/4, pp. 167-177. https://doi.org/10.1108/09556220710741632