Performance prediction of a biobased product
The main materials used in the production of laminated veneer products (LVPs) are wooden veneers which are bonded together with an adhesive under high pressure to a predetermined shape. When a deviation from the intended shape occurs, it poses a major problem for both manufacturers and customers. There is a lot of money to earn and resources to save for the producers and users of laminated veneer products (LVPs) if rejects of LVPs could be reduced. During moulding of LVPs the veneers are exposed to moisture-related stresses and a significant mechanical compression of the thickness.
Previous surveys have indicated that the surface pressure during moulding is often uneven, which may affect the shape stability and strength of the final product. The aim of the present project is to develop a prediction tool for LVPs to make it possible for the industry to improve product performance by reducing rejects and customer complaints and reducing time from idea to market by means of a tool to simulate LVP performance.
To obtain a reliable statistical basis on how the shape stability and strength is affected by different material and process parameters tests will be performed on several small samples. The test results will be used for validation and development of a simulation model of LVPs. The focus of tests are to study both mechanical and structural properties at different times during the curing process and relate them to the cell structure properties of the wood material. The test samples are a variety of selected configurations of LVP moulded in real life to provide the experimental basis for validation of performance of the corresponding virtual product.
This project is focusing on the further development and validation of a fully integrated design optimization process where both the product performance and the producibility of the product is taken into account in the design stage. The project also will build knowledge on how internal properties, primarily material properties, are affected by component geometry and build direction (given the materials and process parameters) in order to build a foundation for how to use this knowledge in the design optimization process for optimal product properties and producibility. This will be done with a focus on periodic surface lattices rather than strut-based lattices.