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A fuzzy approach to using expert knowledge for tuning paper machines

Author

Listed:
  • József Mezei

    (Åbo Akademi University
    Arcada University of Applied Sciences
    Lappeenranta University of Technology)

  • Matteo Brunelli

    (Aalto University)

  • Christer Carlsson

    (Åbo Akademi University)

Abstract

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.

Suggested Citation

  • József Mezei & Matteo Brunelli & Christer Carlsson, 2017. "A fuzzy approach to using expert knowledge for tuning paper machines," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(6), pages 605-616, June.
    • Handle: RePEc:pal:jorsoc:v:68:y:2017:i:6:d:10.1057_s41274-016-0105-3
    DOI: 10.1057/s41274-016-0105-3
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    References listed on IDEAS

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    Cited by:

    1. Christer Carlsson, 2018. "Decision analytics mobilized with digital coaching," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 25(1), pages 3-17, January.

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