Abstract

The continuous pulp production process has been studied for many years because ensuring a high-quality product and high process performance involves multiple considerations and challenges. The objective of this study is to generate an optimization tool for the continuous kraft pulp process by constructing a method to control the operation of the industrial process. The continuous pulp production model is proposed by means of a theoretical method that undergoes multiobjective optimization based on a known metaheuristic, the strong Pareto evolutionary algorithm (SPEA2). The results show that the algorithm can reduce the kappa number standard deviation, enables a yield process increase, and selects the decision variables with a preference that can be changed depending on the market economic context. This allows the use of the algorithm as a model predictive control (MPC) strategy in a continuous digester.