Use of CTL harvester .hpr and .mom files to analyze impact of operator training on productivity
2022
Strubergs, Aigars | Lazdins, Andis | Sisenis, Linards
The study aims to determine the applicability of the StanForD 2010 standard in the analysis of the impact of CTL harvester operator training on productivity. The productivity of harvester operators is affected by factors such as tree species, diameter, type of felling, terrain, operator experience, qualifications, and several other factors. However, there are not many studies that, in addition to the above-mentioned factors, have analysed the impact of periodic training of operators on productivity. The study uses automatically obtained harvester production data from logging service providers. Data are from the John Deere harvester for the period July 2021 to December 2022. The harvester worked in cleaning cutting in the territory of the South Kurzeme forest district. The study used data acquired by two operators who received refresher training during the study period. Harvester Operator No. 1 has work experience of 6 years, and Operator No. 2 has work experience 12 years. Data on the development of four different species of trees in the two months before and two months after the training were used to determine the impact of operator training on productivity. Operator productivity was analysed in three diameter groups for all species and separately for each tree species. The study found that using the automatically obtained data Operator No. 1 and Operator No. 2 average productivity after training increased by 7% and 29%, respectively. However, the effect of different stem diameters and tree species on productivity changes has been found. Operator No. 1 showed a decrease in productivity when processing deciduous trees in separate diameter groups, while Operator No. 2 showed a decrease in labour productivity in some conifer diameter groups. An in-depth data analysis is needed to find out the reasons for the decline in productivity by expanding the data set used.
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