The trim-loss or cutting-stock problem in the paper industry evolves when a large Jumbo-reel is cut into smaller rolls, e.g. end-customer rolls. The standard trim-loss problem does not consider quality deviations when generating the cutting patterns. However, setting up and/or choosing suitable patterns are logical decisions that easily result in a combinatorial explosion of the optimization problem. A number of heuristic-mathematical programming approaches, such as rounding heuristic and column generation have therefore been developed to solve the problem efficiently. Expanding the problem further to efficiently consider quality issues and simultaneously aiming for an optimal or close-to-optimal solution is very challenging and has resulted in only a few contributions in the literature.

During the solution of the initial trim-loss problem, which is closely connected to the production planning, the quality and defect data from various on-line sources along the paper machine does not yet exist. The resulting quality on a paper machine may result in that the initial cutting plan is far from optimal and needs to be re-trimmed. Last year, we introduced a mathematical programming-based two-step approch for solving the quality-based re-trimming problem efficiently and automatically. The approach resulted in optimal or at least close-to-optimal solutions with the effect of a remarkable reduction in quality loss, that is, the economical loss based on degraded quality.

Here, the final approach is briefly presented. A generalization of the model is discussed together with some aspects on the steps how a research result has been implemented to a fully automated product, including challenges and some integration issues. The presentation is concluded by showing some example cases, which show that quality losses may be significantly reduced, leading to a higher throughput, improved customer satisfaction and further savings in a paper mill.