A rough set based decision support approach to improving consumer affective satisfaction in product design

Affective design, also known as Kansei Engineering, is an effective methodology for the study of interactions between human affections and design of products, so as to improve consumer satisfaction. One challenging issue of affective design is to discover the mapping pattern between consumer affections and product design elements from raw design data, which are usually characterised by non-linearity and uncertainty. In view of the insufficiency of traditional methods in dealing with such an issue, this paper proposes a new decision support approach that is based on the principles of dominance-based rough set theory for the study of interactions between consumer affective needs and product features in product design. The proposed approach is able to handle imprecise consumer perceptions and discover latent patterns to guide affective design. The result obtained from an illustrative example shows that the proposed approach provides an effective means to facilitate the affective mapping process and thus is able to improve consumer affective satisfaction with product design. Relevance to industry: This paper proposes an explicit decision support approach to facilitate the affective design mapping process and incorporate consumer affective needs into product design elements, so as to improve consumer affective satisfaction with product design. (c) 2008 Elsevier B.V. All rights reserved.