The objective in this work is to develop a machine learning-based framework for process operability using surrogate responses based on Kriging (also known as Gaussian Process Regression). Currently, the available approaches nonlinear systems are limited by problem dimensionality that they can address, not being computationally tractable high-dimensional systems. proposed approach will use Krigi...