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Funded Projects › H2020

Neural Grader · Neural Grader - Digitizing the Wood Industry

H2020Status: CLOSED1 February 201931 July 2019EU funding €50,000Call H2020-EIC-SMEInst-2018-2020

Fordaq SA has been leading the wood products B2B global market for almost 20 years. We provide our 200.000 user companies with a specialized digital platform for buying products. We have observed how low digitization of the wood industry poses problems for success & often survival for SMEs. There is an urgent need of an automated solution for processing lumber. The current methods are too expensive for SMEs and in practice lead to errors, enormous economic & environmental waste.Our newest product - Neural Grader is the solution to this problem, having the potential of disrupting the European and global wood industry. Its innovation lies in the industrial cameras that capture images of each board and, using state-of-the-art Artificial Intelligence methods, accurately classifies wood quality. Neural Grader also computes the optimal way for cutting the boards and sends commands to the cutting machine, preventing wood waste. Competitive advantages:-Efficiency: it detects defects and grads lumber at high speed, with accuracy that exceeds the one of existing systems;-Affordability: the price will be 1/4 of the price of our competitors’ products, making it accessible for the SMEs, who are currently overwhelmed by overly expensive technology and dominated by large companies;-Full-control of production: companies can manage the production lines and inventory and focus on quality.We have a large base of existing clients and 10 sawmills in Europe & North America sent us Letters of Support (ANNEX 1).Finance: We expect revenue growth of €1.2, €4.4 and €8.3 million in 2020, 2021 and 2022, respectively. Job creation increases from 12 to 29 employees. Operating expenses start at €0.9 million in 2019 and grow to € 2.3 million in 2022.

Consortium · 1 organisation

coordinator

FORDAQ

BE · €50,000

Research fields

View the official record on CORDIS →

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