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Time consumption and productivity in manual tree felling with a chainsaw – a case study of resinous stands from mountainous areas
Author(s) -
Răzvan V. Câmpu,
A. Ciubotaru
Publication year - 2017
Publication title -
silva fennica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.622
H-Index - 60
eISSN - 2242-4075
pISSN - 0037-5330
DOI - 10.14214/sf.1657
Subject(s) - felling , productivity , forestry , consumption (sociology) , geography , tree (set theory) , agroforestry , environmental science , mathematics , art , economics , mathematical analysis , macroeconomics , aesthetics
The purpose of this research is to establish time consumption and productivity when using Husqvarna 365 chainsaw for resinous tree felling in mountainous regions. The research was conducted in the Romanian Southern Carpathians, in two mixed spruce (Picea abies (L.) H. Karst.) and fir (Abies alba Mill.) tree stands (S1 and S2). Only one team of workers, made up of a feller and an assistant, was used in the felling operation. This was divided into nine specific stages for which work times were measured. Work time structure used here includes WP – workplace time (PW – productive work time; SW – supportive work time, NT – non-work time) and NW – non-workplace time. The results indicated a productivity of 10.138 m3 h–1 (4.55 tree h–1) in S1 and of 11.374 m3 h–1 (4.33 tree h–1) in S2. Work time structure was WP 88.61% (PW 19.59%; SW 33.88%; NT 35.14%) and NW 11.39% in S1 and WP 83.77% (PW 17.66%; SW 30.73%; NT 35.38%) and NW 16.23% in S2. The results obtained showed that the power function best describes the relationship between productivity expressed by tree h–1 and breast height diameter (dbh) (R2 = 0.89 in S1 and R2 = 0.94 in S2). When productivity is expressed by m3 h–1 the results obtained in the case of power, exponential and linear functions are comparable (R2 = 0.65 to 0.67 in S1 and R2 = 0.81 to 0.92 in S2). Productivity is also influenced by stump diameter and the distance between trees. Their influence on productivity was emphasized by linear regression equations.

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