One thread of current activities to be intensified in the future is following the objective of predicting and controlling paper properties based on process variables. All approaches are generally data based. Specific outcomes currently available are several soft sensors and model-based control loops operated in paper mills as described earlier. These projects accumulate complex knowledge about the way in which the process has an impact on product quality. To date these projects are individual approaches. An overview and a holistic scientific approach are still missing, these being future tasks for research.
A second thread is dealing with the calculation of paper properties based on the properties of the components defined by the recipe, such as pulp, fillers, and chemical additives. In this field most approaches are fairly generic and include deterministic models. Capabilities of available solutions are very limited. Clearly this is a research area in which a high number of projects are required to cover ground unknown today. One hindering factor for an open scientific exchange in this field seems to be that any breakthrough would give any industrial or scientific player a big edge over competitors. At the same time, despite high investments, none of the research teams has reached a satisfactory level of results within the past 20 years. This in the end could be an impetus towards collaboration in future research.
Looking farther into the future, the main objective of research will then be to interweave these two threads of process – and product-related research into a common web of knowledge. Deterministic process descriptions are currently being used and further developed. As a third strand of research activities, these could help to further improve the applicability of the knowledge gained.
As pulp and paper is based on natural materials processed in a complex way, another task will be to cope with random effects in order to minimise tolerances in mill-level operations, stabilising both product quality and the process. To do this it is required to interpret process data in a statistical context, to do further research to interpret the margin errors, and to more clearly understand process limitations. By combining mathematical models and lab tests, the way from lab to full-scale implementation can be significantly shortened and the possibility to shift between different qualities rapidly increased.
The focus of another area of research will be to describe and optimise the complex pulp and paper value chain on a model-based approach. As a side effect this will bring along the integration of process models with cost models. In the end, this could even prove to be a fourth thread, complementary to the ones described above. The task of future research would be to unveil currently-hidden factors that have an impact on the economic balance of the individual mill as well to interpret the interactions on the socioeconomic and macroeconomic level.
Optimal mill operations result in the optimal use of resources and in an increase of productivity, which means substantial financial benefits. While existing control methods are mainly based on staff experience, models providing better predictability and controllability of the processes would be of considerable value. Therefore, modelling and simulation are important tools to reach the two primary goals of the pulp and paper industry: the decrease of production costs and the increase of the product-added value.
During the past few years many applications for improving the process performance based on controlling different process variables have been implemented at an industrial level; however, the development of models to predict and optimise product properties based on process variables is still in progress. The main difficulty is that papermaking is a highly dynamic process and, in particular, the dynamics of the wet end are still not fully understood. Looking into the future of a knowledge-based process it seems that the interest in model-based control and optimisation will increase, modelling and optimisation of paper properties and model-based paper design will have a very high increase, while process simulation and off-line optimisation will remain the same from the production point of view. However, the equipment and chemical suppliers and consultants will increase the use of these tools to develop the processes and control strategies.