Digitizing Wood

project description

The bending of found 2x4s pulled from waste streams comes with novel challenges that are not encountered when 2x4s are sourced new.  Knots and holes created by nails and screws are liabilities that can be detrimental when bending and twisting forces are applied. (Fig.1) Imperfections are especially problematic where the material is thinnest (at the point of the bend).

Fig.1: Knots, screw-holes, and other imperfections are challenges when bending material.

To counter this problem, HiLo Lab is developing a simulation algorithm to virtually map the zippered tooth pattern onto any given 2×4. Our goal is to determine the optimal tooth placement in relation to any defects identified within the grain of each 2×4. The process involves scanning the face grain of each board using the sensor from an XBOX Kinect. (Fig.2) Once scanned, grain is fed into a computer and analyzed to find the optimal relationship between teeth, each possible member’s unique grain patterns, and any imperfections. The tooth geometry of the zipper leaves large areas of material in place. Once scanned, the image is input into a Grasshopper script that analyses the grain to locate knots and holes (Fig.3). The script then runs an optimization routine through Galapagos, testing the ‘goal regions’ from the zippered tooth surface against the locations of the knots and holes. (Fig.4). We believe the Digitalizing Wood project is novel, will optimize Zippered members, and provide confidence in the use of scavenged materials. It also points to ways designers can leverage computation to further design and production processes.


Fig.2: An XBOX Kinect is forced into duty, scanning stock for analysis.
Fig.3: Grasshopper and Galapagos are used to scan the face, and recognize problems (indicated in red) and benign features (outlined in blue).


Fig.4: The software analyzes the blemishes “recognized” on the face of the wood. It then positions the desired tooth patter to keep veneer locations free of imperfections.



Derek Mavis, Alex Preiss, Graham Entwistle, Blair Satterfield

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