Abstract
Experimental designs are techniques used to determine combinations of design variables to generate models of engineering systems. When experiments are conducted using simulators to determine system responses, the resulting approximation to the simulator is called a metamodel or a surrogate model. Accuracy of metamodels is tightly related to experimental designs. Designs that minimise errors caused by metamodel fitting inadequacy - called bias errors - are known as minimum bias designs (MBDs). This paper presents techniques for generating MBDs for use in response surface metamodelling of engineering systems to obtain minimum bias metamodels. The resulting MBDs are compared to the more recent space-filling designs such as the Latin hypercube (LHC) samples. The paper also includes tables of second-to fourth-order MBDs for two- to five-dimensional spaces.