search project were on new manufacturing concepts (Figure 1). Through the implementation of advanced scanning and optimization technologies it is possible to execute individual sawing operations log by log and to optimize the quality and value of sawn timber and components. This also makes it possible to minimize the amount of low-grade and value timber pieces. According to the research results, by changing the processing concepts it is possible to increase the value of sawn timber production by at least 20 per cent. Halving the faults in manufacturing would provide potential for 10 per cent improvement in the sales value of production. Sorting the logs into homogenous batches to be sawn by a more or less fixed blade setting is a very important part of the sawing process. Log sorting can be upgraded considerable by scanning the geometrical and internal properties of the logs instead of using conventional shape scanning. X-ray measuring technologies have shown to be an effective tool for detecting internal log properties like knots. The classification of logs should be done based on the sawing setup, sawn timber product properties or by picking logs based on their properties. In theory, the best sawing method with regard to value yield is live sawing. Accurate scanning of the log provides information for the optimization of saw blade distances as well as positioning and feeding of the log into the sawing machine. The primary sawing operation produces flitches. After the sawing machine flitches are measured using a multisensory system, the resulting information shows how to split flitches into one or several wooden bars that will be cross cut into the desired lengths. The sawmill company can improve the economic results considerably by moving forward in the value chain and manufacturing value-added wooden components itself or through networking. The sales value of lowquality sawn timber products can be improved by over 100 per cent if they are first converted into component-type products.
The key issue in new production and business concepts is the widespread use of information technology in the management, planning and control of conversion and delivery chains. VTTâ€™s WoodCIMÂŽ simulation and optimization models that support decision-making in the sawmill business applied to the SisuPUU research project are examples of models that can provide radically more information for optimization activities compared with manual planning operations. In the future, there will be many more operation alternatives to choose from than in the present situation. Technologies for identification, i.e. through the marking of pieces, offer the possibility of linking together the products, wood raw material (logs) and processing parameters. It is possible to create feedback information by comparing realized processing results and estimated results. This strongly supports improvements in planning operations, processes and quality control. Based on the feedback information, it is possible to design and implement self-learning systems in which control parameter values are changed if there is a large enough cap between the realized and planned output result. There have to be decision rules for changing parameter values. A data mining approach can be used by developing the rules. In the future, the sawmill will serve refiners and customers much better than today, i.e. by producing precise piece- and batch-based information on the properties of sawn timber and components and by transferring information forwards using making technologies. The results produced in the SisuPUU project provide roadmaps towards the future. Part of the research results can be implemented without heavy investments, for example, by changing boarders of log classes. Part of the practical implementations requires further development, productization and commercialization. Sawmills and technology providers have already shown great interest. Sawmills should execute analyses, as carried out in this research, in order to develop their own business proce-
Production matters. VTT in global trends. Kai Häkkinen (ed.)