为满足产品研发过程中用户的情感需求,从造型设计上最大程度满足用户对产品的情感期望,提出了系统化多意象设计方法。通过BP神经网络计算设计元素组合的多种意象得分,运用AHP方法确定各种意象在用户需求中的权重,最后通过TOPSIS方法确定所有设计元素组合的满意度排序。此外,为弥补AHP法的缺陷,提出对比样本加权意象得分排序与样本优劣排序的方法来确定权重的合理性。以3D打印机造型设计为例,进行多意象设计研究,试验结果表明该方法能够很好地指导产品设计。 To meet the emotional needs of users during product development, the users’ expectation on products is best met from the design of the model, and a systematic and multi-image design method is proposed. BP neural network is used to calculate multiple image scores of design element combinations, AHP method is used to determine the weights of various images in user requirements, and finally, the TOPSIS method is used to determine the satisfaction ranking of all the design element combinations. In addition, in order to make up for the flaw of AHP method, this paper puts forward the method of comparing the ranking of weighted images and the ranking of samples to determine the rationality of weights. Taking 3D printer modeling design as an example, multi-image design is studied. The experimental results show that this method can guide product design well.