Simulation-based Optimization and Decision Support for Papermaking

Pulp and paper industry is facing outstanding challenges in reducing investment and operating costs while aiming at top-quality products and increased production. One of the most cost-efficient ways to advance pulp and paper technologies is to exploit mathematical modeling and computer simulations instead of expensive trials. Moreover, what-if simulation loops can be replaced with automated optimization routines in order to search optimal conditions. In this paper, process optimization is formulated as a mathematical optimization problem to be solved with optimization algorithms. Furthermore, multiobjective optimization methods are used to search for the best possible compromise between numerous contradictory objectives. Simulation-based optimization serves a platform to develop decision support systems for decision makers in papermaking. Here, we describe a realization of such a simulation and decision support tool. We also describe how gradient-based sensitivity analysis and trade-off information helps a decision maker to find his/her preferred optimal solution efficiently. Finally, some numerical examples are given to demonstrate our approach.