Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/27139
Title: AI-based methodology of integrating affective design, engineering, and marketing for defining design specifications of new products
Authors: Kwong, CK 
Jiang, H
Luo, XG
Keywords: Affective design
Chaos optimization algorithm
Fuzzy regression
Marketing
NSGA-II
Issue Date: 2015
Publisher: Pergamon Press
Source: Engineering applications of artificial intelligence, 2015 How to cite?
Journal: Engineering applications of artificial intelligence 
Abstract: 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 (NSGA-II). A case study was conducted for electric iron design to evaluate the effectiveness of the proposed methodology.
URI: http://hdl.handle.net/10397/27139
ISSN: 0952-1976
EISSN: 1873-6769
DOI: 10.1016/j.engappai.2015.04.001
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