Regression Models for the Prediction of Poplar Particleboard Properties based on Urea Formaldehyde Resin Content and Board Density

The aim of this study was to explore the minimum amount of urea formaldehyde (UF) resin content and optimum particleboard density while maintaining boards’ quality to reduce production costs. Board density at three levels (520, 620 and 720 kg m-3) and resin content (6, 7 and 8%) were variable parameters. Stepwise multivariate linear regression models were used to evaluate the influence of board density and resin content on board properties and to determine the most effective parameter. In order to obtain the optimum board density and minimum resin content, contour plots were drawn. Regression models indicated that both board density and resin content were included in Modulus of Rupture (MOR) and Modulus of Elasticity (MOE) models based on the degree of their importance. Internal Bond (IB) model only had one step and resin content positively affected it. The results obtained from contour plots revealed that manufacturing poplar particleboards with density ranging from 600 to 650 kg m-3 and 6% resin would result in boards with mechanical properties within those required by the corresponding standard. Thickness swelling (TS) values were slightly higher (poorer) than the requirements. The panels required additional treatments such as using adequate amount of water resistant materials to improve thickness swelling after 2 and 24 hours of immersion.

Regression Models for the Prediction of Poplar Particleboard Properties based on Urea Formaldehyde Resin Content and Board Density Keywords:

Mechanical and Physical properties , Multivariate-linear regression , Particleboard , UF resin content