A1 Journal article (refereed), original research

A fuzzy approach to using expert knowledge for tuning paper machines


Publication Details

Authors: Mezei Jozsef, Brunelli Matteo, Carlsson Christer

Publisher: Palgrave Macmillan

Publication year: 2017

Language: English

Related journal or series: Journal of the Operational Research Society

Start page: 1

End page: 12

Number of pages: 12

ISSN: 0160-5682

JUFO level of this publication: 2

Digital Object Identifier (DOI): http://dx.doi.org/10.1057/s41274-016-0105-3

Open Access: Not an Open Access publication


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.


Last updated on 2018-19-10 at 07:55