Article ID Journal Published Year Pages File Type
381676 Engineering Applications of Artificial Intelligence 2007 12 Pages PDF
Abstract

The quality of thermomechanical pulp (TMP) is influenced by a large number of variables. To control the pulp and paper process, the operator has to manually choose the influencing variables, which can change significantly depending on the quality of the raw material (wood chips). Very little knowledge exists about the relationships between the quality of the pulp obtained by the TMP process and wood chip properties. The research proposed in this paper uses genetically generated knowledge bases to model these relationships while using measurements of wood chip quality, process parameter data and properties of raw material such as bleaching agents. The rule base of the knowledge bases will provide a better understanding of the relationships between the different influencing variables (input and outputs).

Related Topics
Physical Sciences and Engineering Computer Science Artificial Intelligence
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