xT smart_DoE uses advanced A.I. algorithms to help you find optimal solutions (mixture recipes, machine parameter configurations) in short amount of time without adding unnecessary complexity. Nevertheless, you are still required to make some actual experimental runs - we suggest you try at least some 60 software suggested samples in order to get satisfactory results. The software also allows you to group samples in series, if producing samples can be parallelized.
Our software is designed to operate efficiently in small data environments, where problems are nonlinear and every trial costs you a great deal of resources. Such problems usually are extremely difficult, high-dimensional and lack extensive mathematical models. And this is exactly, where smart_DoE can help you out.
Your application engineers, domain experts and senior researchers can tell a bad solution from a good solution. And that is, what it takes for smart_DoE to improve on its findings. You only need to configure the experiment and tell the software, which of its suggestions are closer to what you anticipate, and then the software will guide you to optimal results in no time.