Process optimization using machine learning

The objective of the response optimization algorithm is to exploit the mathematical model to look for optimal operating conditions. Indeed, the predictive model allows us to simulate different operating scenarios and adjust the control variables to improve efficiency. For a given set of states, determine the controls that minimize or maximize the performance variables. The next figure illustrates the response optimization process. As we can see, for a given state value, s, the control value, c*, minimizes the performance value.