Model-based direct search optimization of the broke recirculation system in a newsprint mill

Abstract

This work is concerned with the dynamic modelling of the papermaking section of an integrated newsprint mill, and the subsequent application of two direct search methods in a proof-of-concept optimization study of broke recirculation strategies. The effect of the current broke recirculation policy on the mixed pulp properties at the paper machine headboxes was quantified using a dynamic simulation generating data for an objective function which reflected the rate of change in measurable (flow, consistency and temperature) and immeasurable (total dissolved solids and fibre length distribution) parameters. Genetic Algorithm and the Nelder–Mead simplex methods were then linked dynamically to the simulation and used to find improved ways of recirculating broke pulp. Specifically, the profile of the changes to the broke ratio was modelled using a quadratic function and a second-order transfer function, and the coefficients of these functions were optimized. The optimized broke recirculation resulted in a significant reduction in the value of the objective function, thus, suggesting that the fluctuations in the properties of the mixed pulp stream could be dampened and paper machine headbox stability improved. It is expected that this process enhancement strategy would contribute to an increase in production yield (via a reduction in the occurrence of paper machine breaks), and thus an overall reduction in the waste of materials and energy.