The article discusses how to create accurate models of engineering systems using experimental designs. These models, called metamodels, are crucial for predicting system behavior. The researchers focus on generating designs that minimize errors in these models, known as bias errors. They compare traditional designs with newer space-filling designs to see which ones work best. The study provides tables of optimal designs for different dimensional spaces, helping engineers create more reliable metamodels for their systems.