Fuzzy Nonlinear Models for New Product Development Using Four-Phase Quality Function Deployment Processes

Quality function deployment (QFD) frameworks are useful tools for constructing a new product development (NPD) plan that enables the clear itemization of customer needs and the systematic evaluation of each solution to maximize customer satisfaction. A complete QFD process includes four sequential phases in which four important decision outcomes are determined for NPD, namely, the fulfillment levels of design requirements (DRs), part characteristics, process parameters, and production requirements. Unlike prior studies which have focused only on determining DRs, this paper extends Chen and Ko's models to consider the close link between the four phases in NPD using the means-end chain concept to build up a series of fuzzy nonlinear programming models for determining the fulfillment levels of each decision outcome for customer satisfaction. In addition, this paper incorporates risk analysis, which is treated as the constraint in the models, into the QFD process. To deal with the vague nature of product development processes, fuzzy sets are applied for both QFD and risk analysis. A numerical example is used to demonstrate the applicability of the proposed model.