Glasnik Šumarskog Fakulteta: Univerzitet u Beogradu (Jan 2018)
The analysis and assessment of productivity in the processing of beech logs on the example of the selected production system in Serbia by applying statistical modeling
Abstract
This paper presents the results of the study of the influence of the selected factors on the productivity of the processing of beech logs on the example of the selected producer of sawn timber in Serbia by applying statistical modeling. The analysis covered three basic factors that have an impact on productivity: the length, middle diameter and number of cuts on the logs of beech that were processed during the observed period. The research was carried out on a sample of 105 logs, and it contained various sizes of middle diameters, lengths and number of cuts. The research aimed to review the functional dependence of selected factors and productivity in order to reach appropriate conclusions, provide expert recommendations and measures to increase productivity and make appropriate forecasts of possible productivity values. In order to examine the functional dependence of the selected variables, statistical modeling was performed in SPSS, v.20 and MS Excel software packages, where the selected dependent variable is the number of logs processed in one hour, and as an independent variable the volume was taken into consideration (which contains the middle diameter and the length of the logs) and the number of cuts. Statistically obtained parameters showed a significant influence of the volume and number of cuts on the change of the number of logs which are processed in one hour. In the obtained regression model the correlation coefficient R is 0.994, while the coefficient of determination R2 = 0.988. Since in sawmill processing productivity is most often expressed as the volume of processed logs in the unit of time, a transformed form of the equation shows the dependence of the volume on the number of logs and the number of cuts. By setting the hypothesis and by interpreting the statistical indicators, it has been found that the impact of the analyzed factors is very high, but that, in addition to them, productivity is influenced by technical and organizational factors.
Keywords