Please use this identifier to cite or link to this item: https://repository.iimb.ac.in/handle/2074/11888
Title: Linking quality function deployment with conjoint study for new product development process
Authors: Chaudhuri, Atanu 
Bhattacharyya, Malay 
Keywords: Conjoint analysis;New product design;QFD
Issue Date: 2005
Publisher: IEEE
Related Publication: 2005 3rd IEEE International Conference on Industrial Informatics, INDIN
Conference: INDIN '05. 2005 3rd IEEE International Conference on Industrial Informatics: 10-12 August, 2005, Perth, WA, Australia 
Abstract: Conjoint Analysis (CA) is a popular marketer's tool for new product design. Quality Function Deployment (QFD) is another approach, frequently used by engineers, for design of new product. Typically, in a conjoint study, the attributes and their levels are determined through Focus Group Discussion or market survey. On many occasions, the researchers leave out some of the more critical features altogether or include attributes with unrealistic sets of levels resulting in infeasible product profiles. In QFD, on the other hand, the New Product Development team attempts to identify the technical characteristics (TCs) that should be improved or included to meet the customer requirements (CRs) by using a subjective relationship matrix between CRs and TCs. QFD is not used to determine the attributes and their levels. As a result, more often than not, QFD captures what product developers "think" would best satisfy customer needs. In this paper, we link QFD with Conjoint and propose a framework for objectively determining the attribute levels using the QFD approach for subsequent use in a conjoint study. For this purpose we obtain the so-called relationship matrix in QFD in a particular way that facilitates achieving our objective. We formulate an integer-programming problem for maximising the weighted sum of improvements in the product, subject to budgetary constraint and minimum percentage improvement for each or some of the attributes. We apply the framework for a commercial vehicle design problem with hypothetical data. © 2005 IEEE.
URI: https://repository.iimb.ac.in/handle/2074/11888
ISBN: 0780390946
9780780390942
ISSN: 1935-4576
2378-363X
DOI: 10.1109/INDIN.2005.1560409
Appears in Collections:2000-2009

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