Evaluation of Particleboard Properties Using Multivariate Regression Equations Based on Structural Factors

The application of stepwise multivariate-linear regression models for determination of particleboard properties based on structural factors was studied. poplar (populus alba), beech (fagus orientaleis) and hornbeam wood (carpinus betulus) with dry density of 460, 630 and 790 kg/m^3, respectively, were used as raw materials. three levels of boards target density (520, 620 and 720 kg m^-3) and urea formaldehyde (uf) resin (6, 7, and 8%) were compared. the variables were included in the regression equations of modulus of rupture (mor), modulus of elasticity (moe), shear strength, and thickness swell (ts) after 24 hours immersion based on the degree of importance. in order to obtain the optimum board density and resin content for each species, contour plots were drawn by minitab 13 software. regarding the results from contour plots, particleboards with density ranging from 520 to 620 kg m^-3 and 6% resin had most of their mechanical properties within those required by the corresponding standards. thickness swell values were higher than requirements. we suggest additional treatments such as using adequate amount of water resistant materials to improve ts after 24 hours immersion.