This study was carried out in a steep and difficult terrain. Trees were logged downhill to the landing by a wheeled skidder Timberjack 450C. Selection cutting was performed on a 66-hectare tract with an average slope of 30%. The elemental time study method was applied to develop the skidding time predicting model. In this study 43 working cycles were included. The skidding cycle time was mainly affected by skidding distance, winching distance and interaction between skidding distance and slope. The gross and net production rate was 20.51 and 22.93 m<sup>3</sup>/h, respectively. The unit cost considering the gross and net production rate was 6.31 and 6.22 USD/m<sup>3</sup>, respectively.
A field production study was conducted for a manual harvesting system using a chainsaw in a Caspian hardwood forest site. A selective cut was performed on a 42-hectare tract with an average slope of 30 percent. Felling time per tree was most affected by diameter at breast height and by the distance among harvested trees. The gross and net production rate was 20.6 m 3 and 26.1 m 3 per hour/one person, respectively. The unit cost considering the gross and net production rate was 1.05 USD/m 3 and 0.81 USD/m 3 , respectively. The significant variables included diameter at breast height (D) and distance among harvested trees (L) for the time expenditure model. This regression function is statistically significant at α = 0.01.
ABSTRACT:Harvester technologies represent the second most common logging system in the Czech Republic. The high productivity of this technology is very necessary to cover its acquisition and operational costs. A human factor -a machine operator is the most important factor that surely influences the machine productivity. That is why the aim of this study is as follows: to analyze the mutual dependence of machine operator's education and working experience and harvester and forwarder productivity. The analysis proves that the operator's education and even more his working experience are very important. The time of harvesting work stages was measured when the harvester was operated by an operator with two-year working experience and by an operator with no experience. The average time difference between the harvester operators was 64.9 seconds in one work stage. The statistical significance of different operation times was confirmed during technically demanding segments in the working stage (the boom out the felling head and tree processing). Operators with the same working experience in forestry mechanization -about 13 years but with different education carried out the haulage work stage. In this case, the statistical significance between calculated differences was not proved. This fact proves that the operator's working experience is more important than his education.
AbstrAct:The aim is to conduct experimental measurements and analyses of physical and mental workload of harvester operators. Among other things, monitoring and analyses of work conditions and workload help reduce possible risks, injuries and long-term illnesses caused by occupational stress. The interim results of the presented ergonomic study describe and analyse the course of physical load upon performing selected work operations at the stage of timber harvesting in laboratory conditions at the harvester simulator. The authors study particularly the relations between independent variables (work operations) and dependent variables (pulse, respiration and muscle tension). The diagnostic system Biofeedback 2000x-pert is used for measuring and recording changes in dependent variables. Results presented in this study analyse the obtained differences in measurements of physical and mental load in operators in individual work operations. The null hypothesis about the non-existence of a difference between the working operations from the viewpoint of the monitored variables can be refused. Therefore we can accept the hypothesis stating that there is a significant difference between individual working operations.
Harvesters produce one third of timber in Czechia. The aim of this study was to analyze the over- and under-bark volume estimates of Scots pine (Pinus sylvestris L.) timber produced by a mid-performance harvester. The data were collected between March 2017 and June 2018. In total, 4661 stems cut into 29,834 logs were analyzed. For volume estimation, StanForD offers several price categories using various algorithms. Three of these price categories are relevant for Czech forestry—M3s, M3toDE, and M3miDE. The M3s price category is based on the estimation of partial volumes of 10 cm long sections, which are summed. Therefore, this price category represents the volume estimation closest to the true volume. By comparison, the M3toDE and M3miDE price categories use the same algorithm for volume estimation, which is based on the Huber formula using a midspan diameter rounded down to the nearest whole centimeter. The M3toDE price category underestimated the over-bark volume by 6.48% compared to the reference price category M3s. The mean log volume estimated through the M3s price category was significantly higher than the M3toDE volume both in individual grades and without grading. We found significant differences between under-bark volume estimates by the diameter band bark deduction method (DBM) and the parametric linear bark deduction method (PLM) used in harvester’s systems according to the Guidelines for Electronic Scaling of Timber for Harvesters in Czechia (GEH) for Scots pine butt logs with rough bark, and also for other logs with normal bark thickness. To obtain under-bark volume estimates of Scots pine timber that are comparable with the Guidelines for Timber Scaling in Czechia (GTS) using the parametric nonlinear bark deduction method (PNM), we recommend using the algorithm of the M3toDE price category, with double bark thickness determined by the diameter band bark deduction method.
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