An ISM-BN-GA based methodology for product emotional design

Most current studies of product emotional design (PED) focus on the association of emotion image with a single design feature. However, these studies have ignored the fact that all product features have a combined effect on emotion image, and have also ignored the relationship between the whole and the part. In view of this, starting from the systematicness of design, PED is translated to the solution of the PED system. Moreover, an ISM-BN-GA-based methodology for PED is proposed. First, the sense perception–perceptual cognition–perceptual synthesis–emotional decision (PCSD) cognitive model is developed based on the process of user emotion transmission, based on which a pedigree of the elements in the PED system is constructed. Second, a multilevel hierarchical directed network of the elements in the PED system is established using the interpretation structure model (ISM) system engineering tool, and the network topology is extracted as the network structure of a Bayesian network (BN). Then, the BN is trained via parameter learning, and the evaluation model of the PED system based on the ISM-BN is constructed. Third, with the ISM-BN evaluation model as the objective function, a genetic algorithm (GA) is used to search for the optimal design scheme. Taking the design of a handheld camera as an example, the validity of the proposed method is verified, which proves its feasibility and practicability in the field of PED.