**7.3 Artificial neural networks (ANN)**

Machine-based computational methods called Artificial Neural Networks (ANNs) aim to imitate some of the neurological processing capabilities of the human brain. Because of their nonlinear processing power and capacity to simulate complex systems, ANNs have special advantages [33–37]. The results are equivalent with superior prognostic capabilities when compared to other optimization techniques. However, they are rather challenging to apply to more levels or elements, and no statistical criterion is made clear to indicate the level of applicability of the model.

### **7.4 Extrapolation outside the domain**

For first order designs, steepest ascent (or descent) methods are direct optimization techniques [38], particularly when the optimum is external to the domain and needs to be reached quickly. The optimum path method, which is employed for extrapolating the optimum outside of the experimental region, is just like the steepest ascent approach. Several industrial processes use the evolutionary operations technique, which allows the production procedure (formulation and process) to evolve to the best possible state through careful planning and repeated repetition.
