CORDIS provides links to public deliverables and publications of HORIZON projects.
Links to deliverables and publications from FP7 projects, as well as links to some specific result types such as dataset and software, are dynamically retrieved from OpenAIRE .
Exploitable results
The Saw Mill of the Future:
In this project, Intelligent Manufacturing techniques are applied to design and implement advanced technology for the year 2000 wood manufacturing plants. The project brings together a consortium of SMEs, Universities, and non-SME end-user companies to advance the state-of-the-art in the area of automatic quality assurance in present and future wood manufacturing plants. In this context, quality assurance aims at the on-line inspection, grading, optimisation, and intelligent fusion of the measured parameters. The goal is efficient utilisation of wood as a precious raw material, and to reduce production costs through a high degree of automation.
Existing systems for wood grading are limited in performance by two factors: First, their accuracy suffers from the use of just one type of sensor. Secondly, the processing and image analysis algorithms are rather simple, and totally neglect the present advances in computer vision and image analysis. Consequently, the achieved accuracy is insufficient. Every single sensor has its disadvantages, which cannot be eliminated, even through very careful development and optimisation.
Under this project, various conventional, and several novel sensors were advanced and developed to push the current state-of-the-art in on-line measuring, and solve many of the present problems. Our approach was to replace the present single-sensor approach with a multi-sensor approach, and work on the combination of colour CCD-cameras, Laser-based Tracheid sensors, smart sensor systems, X-ray imaging, and Computer-Tomography imaging, to build four modular, high performance prototype systems. On the processing level, modern results in image analysis should be implemented. This includes neural network techniques, genetic algorithms, and modern statistical approaches.
The unique combination of the SME companies forming the project team is the primary reason for the achieved economic success. After the successful completion of the project, the consortium has in its possession system components that did not previously exist, and which have extremely improved performance parameters. Through the emphasis on modularity, the system can be marketed in a wide range of applications. We installed six prototype systems, which demonstrate the intelligent approach to wood manufacturing. Marketing of the system will be done by the consortium members themselves, or through licensing of all or several components to third parties.
Due to the global shortage, wood as a raw material has been in strong demand. Recent statistics show that many companies suffer greatly from the diminishing supply. Due to the strong potential of reducing unnecessary waste, the project contributes to the global economic and ecologic situation. The accurate and robust detection of defects will enable the manufacturing plants to decrease waste, while increasing the quality of the produced goods.
We have reached several successful installations of high-speed image processing systems showing the feasibility of on-line texture analysis. Other prototype systems are equipped with a smart sensor system fusing the texture analysis with the smart sensor output.
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