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European Journal of Wood and Wood Products

Erschienen in:

06.12.2023 | Original Article

Big data analysis on manufacturing variables affecting properties of medium density fiberboard

verfasst von: Seongsu Park, Byung-Dae Park, Yongku Kim

Erschienen in: European Journal of Wood and Wood Products | Ausgabe 2/2024

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Abstract

The properties of medium density fiberboard (MDF) panels manufactured by reconstituting wood fibers and binders under high temperature and pressure depend on various manufacturing variables, including wood-related parameters, adhesive-related ones, and process-related ones. This study focused on the analysis of big data (about 400 million data) of the manufacturing variables (1389 variables) of MDF panels to understand the influence of these variables on the properties of MDF, using Ridge, Lasso, and Elastic-net regression. Both Lasso and Elastic-net regression were better than Ridge one in predicting the properties of MDF. The analysis results also showed that flash tube dryer, mat forming, and hot-pressing variables were closely related to panel density while fiber bin, refiner, forming, press, and hot-press heating variables affected the modulus of rupture (MOR) of the MDF panel. The analysis of interactions between manufacturing variables and MDF properties showed that the panel density affected internal bond (IB) strength, core density, and moisture content while IB strength and moisture content were associated with the MOR of the MDF panel. However, it is not clear which variables are dominantly affecting the formaldehyde emission of MDF.

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Titel: Big data analysis on manufacturing variables affecting properties of medium density fiberboard
verfasst von: Seongsu Park
Byung-Dae Park
Yongku Kim
Publikationsdatum: 06.12.2023
Verlag: Springer Berlin Heidelberg
Erschienen in: European Journal of Wood and Wood Products / Ausgabe 2/2024
Print ISSN: 0018-3768
Elektronische ISSN: 1436-736X
DOI: https://doi.org/10.1007/s00107-023-02030-6

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