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Intelligent maintenance and performance optimization of forest machines with soft-sensor methods

In the cut-to-length harvesting method, which is dominant in Scandinavia, a harvester and a forwarder work as a pair. The harvester fells and delimbs the trees and cuts them to logs such that the value of the wood is maximized. The forwarder then carries the logs to the roadside for further transportation. The working conditions of the machines are very demanding: in the forest the weather can change from one extreme to an other during one work shift. Seasonal changes and differences between the trees in different stands are also major factors affecting the performance and productivity of the machines. To minimize downtime and to keep the machines in perfect working condition all the time, appropriate and appropriately scheduled maintenance is necessary. In the project new methods are studied for monitoring and improving the performance, usability and dependability of forest machines.

This project is part of SOSE.

Our research partner is the Institute of Automation and Control (ACI) of the Tampere University of Technology (TUT). Our industrial partner is John Deere Forestry / Plustech. Our research is financed by Tekes and John Deere Forestry / Plustech.



Master's Theses

  • Lauri Palmroth: Adaptive stem grasping in tree delimbing (2002, TUT)