AbstractDesign of experiments (DoE) is a family of methods for performing experiments that are maximally informative for a chosen mathematical model. Statistical design of experiments focuses on empirical models that are sufficiently flexible as to describe a wide variety of systems, while having favorable mathematical properties for convenient estimation and optimization. This review describes approaches in statistical DoE for screening through many potential influencing factors and finding optimum process conditions.