The Usage of Regression Models for Prediction of the Effects of Wood Species Density and Board Density on One Layered Particleboard Properties

Document Type : Research Paper

Authors

1 Professor, Department of Wood and Paper Science and Technology, Faculty of Natural Resources, University of Tehran, Karaj, I.R. Iran

2 Ph.D. Student, Department of Wood and Paper Science and Technology, Faculty of Natural Resources, University of Tehran, Karaj, I.R. Iran

3 Graduated MSc., Department of Wood and Paper Science and Technology, Faculty of Natural Resources, University of Tehran, Karaj, I.R. Iran

Abstract

board density by regression models, this study was carried out. Regarding two variables: wood dry
density (460, 630 and 790 Kg/m3) and board density (520, 620 and 720 Kg/m3) one layer
particleboards were made. Board properties such as MOR, MOE, shear strength, water absorption and
thickness swelling (after 24h immersion) were measured. Stepwise multivariate regression models
were used to evaluate the effect of the above variables on board properties and to determine the most
effective parameter. Equations indicated that both two factors affected the models of MOR, shear
strength, WA and TS based on the degree of their importance. The effect of the variables on MOE was
not significant. Results from minitab contour plots revealed that increase in board density caused to
improvement mechanical properties. Regarding the shortage of initial wood resources, it is possible to
making particleboards with density of 520 - 620 kg/m3 with mechanical properties within those
required by corresponding EN standard. TS values were higher than requirements. Panels required
additional treatments such as using amount of water resistant materials.

Keywords

References

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