Swarm-Optimization-Based Affective Product Design Illustrated by a Mobile Phone Case-Study

Abstract

This paper presents a new approach of useroriented design for transforming users' perception into product elements design. An experimental study on mobile phones is conducted to examine how product form and product design parameters affect consumer's perception of a product. The concept of Kansei Engineering is used to extract the experimental samp les as a data base for neural networks (NNs) with particle swarm optimizat ion (PSO) analysis. The result of numerical analysis suggests that mobile phone makers need to focus on particular design parameters to attract specific target user groups, in addition to product forms. This paper demonstrates the advantage of using KE-PSO for determin ing the optimal co mbination of product design parameters. Based on the analysis, we can use KE-PSO to suggest customers' preferences for mobile phone design attributes that would be considered optimal by various user groups of all surveyed. They can be used for improvement and development of new future products.