A combined QFD and Fuzzy integer programming framework to determine attribute levels for conjoint study
Bhattacharyya, M.; Chaudhuri, A.
N.R. Srinivasa Raghavan
John A. Cafeo
In a recent paper, Chaudhuri and Bhattacharyya propose a methodology combing Quality Function Deployment (QFD) and Integer Programming framework to determine the attribute levels for a Conjoint Analysis (CA). The product planning decisions, however, are typically taken one to two years before the actual launch of the products. The design team needs some flexibility in improving the Technical Characteristics (TCs) based on minimum performance improvements in Customer Requirements (CRs) and the imposed budgetary constraints. Thus there is a need to treat the budget and the minimum performance improvements in CRs as flexible rather than rigid. In this paper, we represent them as fuzzy numbers instead of crisp numbers. Then a fuzzy integer programming (FIP) model is used to determine the appropriate TCs and hence the right attribute levels for a conjoint study. The proposed method is applied to a commercial vehicle design problem with hypothetical data.
The Art and Science Behind Successful Product Launches (243-256). Springer Verlag. https://doi.org/10.1007/978-90-481-2860-0_13
|Deposit Date||Sep 14, 2019|
|Book Title||Product Research:
The Art and Science Behind Successful Product Launches
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