A decision model for setting target levels in quality function deployment using nonlinear programming-based fuzzy regression and optimization

Abstract

Quality function deployment (QFD) is a customer-oriented design tool for developing new or improved products and services to increase customer satisfaction. The inherent fuzziness of functional relationships between customer requirements and engineering characteristics, and among engineering characteristics in QFD modeling justifies the use of fuzzy regression. However, when linear programming is used in fuzzy regression, spread values of regression coefficients tend to approach zero. In order to overcome this problem, this paper employs a nonlinear-programming-based fuzzy regression approach to model functional relationships in product planning. Then, a fuzzy mathematical programming model is developed to determine target levels of engineering characteristics using the functional relationships obtained from fuzzy regression. Fuzzy mathematical programming model enables to account for the spread values as well as the center values of the parameter estimates of the functional relationships. A washing machine quality improvement problem is presented to illustrate the application of the proposed approach.