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Defectless

If a piece of precious wood has defects, it cannot be used to make certain objects, but some others can be made avoiding the defect zone.

Goals: 
Aim of the project is to utilize at best the wood blocks by reducing discards. This is performed by introducing a new software module in the mechanical process that from walnut blanks conducts to the production of specific pieces. The software receives in input the slices acquired by a tomograph through which the wood transits before to be passed to the next machine of the production line. A 3D shape of the wood block is reconstructed and a deep-learning neural net classifies the voxels into good or defect class. A priori knowledge of the 3D designs of each single product and its characteristics permits to choice the most suitable one to be built from that block.
Date: 
Monday, 26 November, 2018 to Saturday, 25 January, 2020
Duration: 
14m
Partners: 
Funding: 
LP 6
Unit role: 

Develop software to detect and classify defects in wood and optimize the position of models inside it.