AI-based methodology of integrating affective design, engineering, and marketing for defining design specifications of new products

被引:64
|
作者
Kwong, C. K. [1 ]
Jiang Huimin [1 ]
Luo, X. G. [1 ,2 ]
机构
[1] Hong Kong Polytech Univ, Dept Ind & Syst Engn, Hong Kong, Hong Kong, Peoples R China
[2] Northeastern Univ, Sch Informat, Dept Syst Engn, Shenyang, Peoples R China
关键词
Affective design; Marketing; NSGA-II; Fuzzy regression; Chaos optimization algorithm; CUSTOMER SATISFACTION MODELS; FUZZY REGRESSION APPROACH; LINE DESIGN; GENETIC ALGORITHM; NEURAL-NETWORK; FORM DESIGN; LOGISTIC-REGRESSION; CONJOINT-ANALYSIS; FAMILY DESIGN; MOBILE PHONES;
D O I
10.1016/j.engappai.2015.04.001
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In the early stage of product design, particularly for consumer products, affective design, engineering, and marketing issues must be taken into considerationand they are commonly performed respectively by product designers, engineers, and marketing personnel. However, they have different concerns and focuses with regard to the new product design. Thus, these three processes are commonly conducted separately, leading to a sub-optimal and even sub-standard design. Such scenario indicates the need to incorporate the concerns of the three processes in the early stage of product design. However, no study has explored the incorporation of the concerns of the three processes into the product design. In this paper, an artificial intelligence (AI)-based methodology for integrating affective design, engineering, and marketing for defining design specifications of new products is proposed by which the concerns of the three processes can be considered simultaneously in the early design stage. The proposed methodology mainly involves development of customer satisfaction and cost models using fuzzy regression, generation of product utility functions using chaos-based fuzzy regression, formulation of a multi-objective optimization model and its solving using a non-dominated sorting genetic algorithm-II (NSGAII). A case study was conducted for electric iron design to evaluate the effectiveness of the proposed methodology. (C) 2015 Elsevier Ltd. All rights reserved.
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页码:49 / 60
页数:12
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