Comparison of small sized designs for second-order models

Abstract

Response surface methodology (RSM) is a useful collection of experimentation techniques for developing, improving, and optimizing products and processes. When we are to estimate second-order regression model and optimize quality characteristic by RSM, central composite designs and Box-Behnken designs are. widely in use. However, in developing cutting-edge products, it is very crucial to reduce the time of experimentation as much as possible. In this paper small sized second-order designs are introduced and their estimation abilities are compared in terms of D-optimality, A-optimality, and the number of experimental runs. The result of this study will be beneficial to experimenters who face experimental circumstance which are expensive, difficult, or time-consuming. Significance: Small sized designs are introduced and compared in terms of some criteria. The results will be beneficial to engineers working on cutting-edge product development.