A fuzzy approach to using expert knowledge for tuning paper machines

Paper machines are very complex production systems, but their scope is simple: they consume materials and resources, called factors, to produce paper, which in turn can be described by its characteristics. In this paper, a decision support system is developed in cooperation with an industrial partner to help them with operational decision making when tuning a paper machine. The decision support system was developed in two phases. Firstly, the knowledge of experts is collected and stored in the form of a fuzzy ontology. Secondly, this knowledge is made usable so that a user of the decision support system can specify what characteristics of the produced paper to increase or to decrease and be returned with a recommendation on what factors to change. In this paper, we will work out the optimization problems on which the system is based. Additionally to a basic goal programming model, two extensions are explored, accounting for uncertainty and non-linearity, respectively.