Again, equidistant level selection is compared to experimental design. In addition, a full factorial and a Latin-square approach are evaluated. From the simulation
case studies presented, it can be stated that all parameters can be equally well defined from an equidistant design as from a D-optimal-based design. In addition, reducing the experimental load by constructing a Latin-square design does not hamper the parameter estimation procedure. This work confirms the observation of a previous study, i.e., for complex cases a Latin-square design is an attractive
alternative for a full factorial design as it yields equally accurate and reliable parameter estimates while
reducing the experimental workload.