Abstract:

Objectives

To utilise wood raw material efficiently is a difficult problem. Principally because of the great variation in wood qualities and the fact that these most often are not sufficiently known until the final board is at hand; nor are the end manufacturers' real needs sufficiently known at an early stage in the material chain. Therefore, more forest raw material than necessary is harvested in order to produce the amounts of final products wanted. Furthermore, by-products that are unwanted and difficult to sell are also produced. This leads to high costs for both manufacturer and consumer and means that valuable forest material is harvested in a sub-optimal way.

Several methods of judging the potential quality of logs are in use, most of them based on statistical comparison between amounts of logs and amounts of boards by matching distribution of properties. Sensors evaluating the quality of wood have become more and more elaborate. These include X-ray systems for inspecting logs and vision systems for grading boards. Since wood quality is based on several individual, rather than a few bulk, properties and the properties are often dependent on each other in a complex way, the problem still exists. Therefore statistical comparison between bulk properties does not work. Hence, a method for handling detailed and comprehensive enough data is needed that can treat many parameters in a sufficient way.

Contacts

Coordinator

• Richard UUSIJARVI / AB Traetek Swedish Institute for Wood Technology / SWEDEN

Participant

• Johannes RESSMANN / Albert-Ludwigs-Universität Freiburg Institut für Waldwachstum / GERMANY
• Bo AXELSSON / Bohult Maskin AB SWEDEN
• Jean-Pierre OLGIATI / CIRIS FRANCE
• Didier PISCHEDDA / Centre Technique du Bois et de l'Ameublement (CTBA) Departement Bois & Sciage / FRANCE
• Centro de Biomassa para a Energia (CBE) PORTUGAL
• René CLAUDE / ESCOBOIS FRANCE
• Anders GRÖNLUND / Luleaa University of Technology SWEDEN
• Arto USENIUS / Techincal Research Centre of Finland VTT / FINLAND
• Johan MÖLLER / The Forestry Research Institute of Sweden SWEDEN
• Timberjack/Plustech Oy FINLAND
• Eduardo TOLOSANA / Universidad Politécnica de Madrid EUIT Forestales / SPAIN