Analyzing the antecedents and consequences of manual log bucking in mechanized wood harvesting
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CitationKärhä Kalle. Änäkkälä Jyri. Hakonen Ollipekka. Palander Teijo. Sorsa Juha-Antti. Räsänen Tapio. Moilanen Tuomo. (2017). Analyzing the antecedents and consequences of manual log bucking in mechanized wood harvesting. Mechanics, Materials Science and Engineering, 12, 1-15. 10.2412/mmse.45.20.957.
The study focused on the frequency of applying a manual tree-stem bucking to logs in coniferous forests of Finland. The aim of the study was to clarify harvesting conditions where manual log bucking is utilized most and the effects of the utilization of manual bucking on the log bucking outcome. In addition to the stm Big Data of harvesters, in order to investigate the consequences of manual log bucking, data from the enterprise resource production (ERP) systems of wood procurement organization and sawmills was collected, as well as harvester operators were interviewed. The study results illustrated that the share of manual bucking of Norway spruce (Picea abies L. Karst.) logs was, on average, 46% and with Scots pine (Pinus sylvestris L.) logs 67%. The operators used manual bucking more frequently in thinning stands with small-sized and defected log stems. When the utilization degree of manual log bucking was high, the utilization of log sections with spruce and pine log stems was lower, logs were shorter and the volume of logs was smaller. Furthermore, log percentage and apportionment degree were significantly lower when the shares of manual log bucking were higher. The relative production value of spruce logs was lower, and correspondingly the relative production value of pine logs was higher when applying plenty of manual bucking. On the basis of the study results, it can be recommended that nowadays the target for the manual log bucking percentage with spruce must be less than 20–30% of the total log volume cut. In the future, our aim must be fully automatic or semi-automatic and harvester computer-aided bucking based on the quality grades of the log section zones of log stems with pine and spruce. It will require equipping harvesters with novel mobile laser scanning (MLS) and machine vision (MV) applications.