Abstract
Authors: Felicien Kanyamibwa, David P. Christy, & Duncan K.H. Fong
A key element in off-line quality control is to identify the best set of variables to use in designing a product that will meet customers’ expectations. Given the multidimensional nature of quality, this set of variables is not easy to identify. Indeed, the variables of interest as determined by the customers are often numerous and not precise. In this article, a procedure of selecting those variables that make a product a winner in the market for its quality, and for further consideration in the product or process design, is proposed. Specifically, the authors show how the information collected using the quality function deployment technique may be incorporated into a Bayesian variable selection model. The choice of the Bayesian setting is guided by the requirement of flexibility and practical importance of variables in the final model specification, especially ensuring the inclusion of the customers’ requirements in the product design.
https://www.tandfonline.com/doi/abs/10.1080/10686967.2001.11918938
