Product form design model based on the robust posterior preference articulation approach

Affective responses reflect consumers’ affective needs and have attracted considerable attention in industrial product form design. When designing a product for consumers, designers should take into account multiple affective responses. Therefore, designing products that can satisfy multiple affective responses is a multi-objective optimization problem. In this article, a novel model based on the robust posterior preference articulation approach is proposed to optimize product form design by simultaneously considering multiple affective responses. First, design analysis is performed to determine design variables and affective responses. Subsequently, the Taguchi method is used, and the signal-to-noise ratios are calculated. Based on the results, predictive models for signal-to-noise ratios concerning multiple affective responses are built and then a multi-objective optimization model is constructed. The reference-point-based many-objective non-dominated sorting genetic algorithm–II (called NSGA-III) is used to solve the multi-objective optimization model for obtaining Pareto solutions. Finally, a combination of the fuzzy Kano model and the fuzzy optimum selection model is adopted to select the optimal solution from the obtained Pareto solutions. A car profile design was employed to present the proposed approach. The results reveal that the proposed approach can effectively achieve an optimal design and is a robust approach for optimizing product form design.