Title
Soliciting customer requirements for product redesign based on picture sorts and ART2 neural network
Abstract
Design knowledge acquisition plays an extremely important role in new product conceptualization and product redesign. This study aims at facilitating the effectiveness of product redesign activities. It involves two interrelated phases, namely customer requirements elicitation and customer requirements evaluation. Sorting techniques, picture sorts in particular, have been employed for customer requirements acquisition during product redesign process. By applying such a systematic knowledge or requirements acquisition technique, some objectives and constraints of product redesign can then be identified. Furthermore, it has become an imperative to quantitatively and automatically analyze the elicited customer requirements so as to simplify and optimize the subsequent product conceptualization and selection of conceptual design alternatives. For this purpose, the adaptive resonance theory, especially ART2, neural network has been utilized for the preliminary design decisions, such as customer segmentation, in terms of customer requirements evaluation. A case study on the mobile hand phone redesign is used to demonstrate and validate this approach.
Year
DOI
Venue
2008
10.1016/j.eswa.2006.08.036
Expert Syst. Appl.
Keywords
Field
DocType
picture sorts,art2 neural network,product redesign,product redesign activity,soliciting customer requirement,new product conceptualization,requirements acquisition technique,customer segmentation,customer requirements acquisition,picture sort,customer requirements evaluation,elicited customer requirement,customer requirements elicitation,product redesign process,conceptual design,neural network,adaptive resonance theory
Design knowledge,Market segmentation,Voice of the customer,Computer science,Knowledge management,Artificial intelligence,New product development,Customer intelligence,Conceptual design,Requirement,Market requirements document,Machine learning,Process management
Journal
Volume
Issue
ISSN
34
1
Expert Systems With Applications
Citations 
PageRank 
References 
10
0.66
10
Authors
3
Name
Order
Citations
PageRank
Meng-Dar Shieh11079.82
Wei Yan2100.66
Chun-Hsien Chen347264.61