Application of combined Kano model and interactive genetic algorithm for product customization

Interactive genetic algorithms (IGAs) have been applied in industrial design to quickly respond to customers’ personalized demand and to achieve customization. However, unreasonable recognition and improper configuration of customization attributes may increase the design complexity, impair efficiency and lead to user fatigue. In this paper, a combined Kano model and IGA approach is proposed for more effective product customization to conduct customer-driven product design by fully considering their individual preferences and simultaneously enhancing effective user involvement. The approach uses the Kano model to recognize different customization attributes and rank them in order of their influence on customer satisfaction. The model then dynamically adjusts these attributes for customization in the IGA-based product design process to more quickly find a satisfying design scheme without leading to user fatigue. A computer-aided design system prototype is developed in the context of the customized design of tablet PCs to prove the maneuverability and effectiveness of the proposed approach. The experimental results demonstrate that the approach could improve customization efficiency to a large extent and fully relieve user fatigue by expediting the process of finding satisfying design individuals for customers.