Development of design system for product pattern design based on Kansei engineering and BP neural network

Abstract

Purpose

In order to help companies better grasp the perceptual needs of consumers for patterns, so as to carry out more accurate product pattern development and recommendation, this research develops a product pattern design system based on computer-aided design.

Design/methodology/approach

First, use the Kansei engineering theory and method to obtain the user's perceptual image, and deconstruct and encode the pattern based on the morphological analysis method, then through the BP neural network to construct the mapping relationship between the user's perceptual image and the pattern design elements, and finally calculate and find the corresponding design code combination according to the design goal to guide the pattern design.

Findings

Taking costume paper-cut patterns as an example, the feasibility of this system is verified, the design system can well reflect the user's perceptual image in the pattern design and improve the efficiency of pattern customization service.

Originality/value

Compared with the traditional method that relies on the designer's personal experience to propose a design plan, this research provides scientific and intelligent design methods for product pattern design.

Citation

Chen, D. and Cheng, P. (2022), "Development of design system for product pattern design based on Kansei engineering and BP neural network", International Journal of Clothing Science and Technology, Vol. 34 No. 3, pp. 335-346. https://doi.org/10.1108/IJCST-04-2021-0044