Abstract
The aim was to model and identify the most productive cutting methods by comparing forward felling technique (C) with sideways techniques outside (A and D) or inside cutting edge (B and E). First, drone video material of each tree was analyzed by comparing time distributions of work phases. Then, the relation between this input data and harvester’s production data was analyzed by regression models. A Quadratic model predicted the productivity precisely (R2 = 0.95). This model explained the effective-hour productivity in cutting cycle with dummy variables of harvesting conditions. The productivity was explained by tree size and cutting cycle time, while effects of operator and harvester were eliminated successfully according to statistical analysis. In the pine (Pinus taeda) plantations on flat terrain, cutting method B was 4.8 m3/E0h more productive than method A, and 6.7 m3/E0h more productive than method C. In eucalyptus (Eucalyptus saligna) plantations cutting method E was identified 1.8 m3/E0h more productive as compared to cutting method D on sloping terrain. Of the time-cycle variables, time consumption of the “moving of tree” changed statistically most significantly between the cutting methods, of which the methods that used sideways felling technique inside cutting edge were most efficient. This modeling structure can be recommended for precise work studies in similar harvesting conditions.