• Refine Query
  • Source
  • Publication year
  • to
  • Language
  • 1
  • Tagged with
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Investigating the process parameters that influence the z-strength of liquid paperboard using data mining and machine learning

Thaung Tolförs, Gustav January 2021 (has links)
Parameters affecting the z-strength of liquid paperboard (LPB) has been analyzed and identifiedusing data mining and machine learning on 6 years of operational data from a multi-ply LPB mill, and control and stabilizing of them was proposed. Linear regression models were built for 9 articles with satisfactory results, and whose attributes were further analyzed as the most important parameters for the z-strength. The results show that generally only parameters affecting the weakest position in the paperboard has any influence on the z-strength, with unbleached softwood pulp refining work affecting the strength the most, while bleached hardwood refining work has a lower influence, and refining work of bleached softwood has almost no influence on the z-strength. Among the other parameters shown to influence the z-strength are kappa number, headbox concentration, broke ratio, strength and retention starches, fractionation and degree thereof, and the conductivity of the process water.

Page generated in 0.0555 seconds