M. Saarilahti, E. Bakena, G. Mboya, T. Minja, T. Ngerageze, J. Ntahompagaze. (1987). Studies on Tanzanian forest work. Silva Fennica vol. 21 no. 2 article id 5314. https://doi.org/10.14214/sf.a15471

Keywords: logging; time study; heart rate; work load; forest work; production rate; Africa; performance rating; manual timber cutting; sulky skidding; energy expenditure

Abstract | View details | Full text in PDF | Author Info

Four teams of two workers were time-studied in clearcutting of a cypress plantation and three teams in sulky skidding. The heart rate was recorded every 30 s. The average heartrate in timber cutting was 117.5 ± 13.4 P/min, and it was mainly dependent on worker’s working capacity. Average work load index was 41 ± 3% when working at 97% performance. The production rate was then 2.5 m³/h (crew). In sulky skidding the heart rate was lower, 106 ± 1.1 P/min, as well as the work load (WLI 30 ± 1%) and performance rating (87%). The low production rate (1.1 m³/h) (crew)) over 45 m distance is mainly due to under-dimensioned load size. The energy expenditure in timber cutting was 21.4 kJ/min and in sulky skidding 16.3 kJ/min. Daily energy expenditure was 15.0 MJ/d, and most of the timber cutters belonged to the class ”exceptionally active”.

The PDF includes an abstract in Finnish.

Saarilahti, E-mail: ms@mm.unknown
Bakena, E-mail: eb@mm.unknown
Mboya, E-mail: gm@mm.unknown
Minja, E-mail: tm@mm.unknown
Ngerageze, E-mail: tn@mm.unknown
Ntahompagaze, E-mail: jn@mm.unknown

article id 5059, category Article

Pertti Harstela. (1980). Jäljelle jäävä puusto ja ajouralta toimivat harvennuspuun korjuukoneet. Silva Fennica vol. 14 no. 1 article id 5059. https://doi.org/10.14214/sf.a15000

English title: Remaining trees and machines working from the strip roads in thinning.

Original keywords: harvennushakkuu; puunkorjuu; metsäkoneet; ajourat; jäljelle jäävä puusto; valikoiva harvennus

English keywords: skidding; thinning; timber harvesting; forest machines; strip roads; remaining trees

Abstract | View details | Full text in PDF | Author Info

In the first part of the study the hindrance of the remaining trees when felling trees by machines working from the strip road in selective thinning was studied on the basis of the literature. In the second part there was geometrically studied the need of schematic thinning in some type stands when bundles are pre-skidded straight-lined to the strip road. In average only 0-1 trees per pre-skidding trail needs to be removed. It was concluded that trees removed from the pre-skidding trail do not significantly increase the need of schematic thinning. Remaining trees do not limit the length of machine booms if the pre-skidding trails are planned during the felling.

The PDF includes a summary in English.

Harstela, E-mail: ph@mm.unknown

Category : Research article

article id 57, category Research article

Corrado Costa, Paolo Menesatti, Raffaele Spinelli. (2012). Performance modelling in forest operations through partial least square regression. Silva Fennica vol. 46 no. 2 article id 57. https://doi.org/10.14214/sf.57

Keywords: chipping; productivity; harvesting; skidding

Abstract | View details | Full text in PDF | Author Info

Partial Least Square (PLS) regression is a recent soft-modelling technique that generalizes and combines features from principal component analysis (PCA) and multiple regression. It is particularly useful when predicting one or more dependent variables from a large set of independent variables, often collinear. The authors compared the potential of PLS regression and ordinary linear regression for accurate modelling of forest work, with special reference to wood chipping, wood extraction and the continuous harvesting of short rotation coppice. Compared to linear regression, PLS regression allowed producing models that better fit the original data. What is more, it allowed handling collinear variables, facilitating the extraction of sound models from large amounts of field data obtained from commercial forest operations. On the other hand, PLS regression analysis is not as easy to conduct, and produces models that are less user-friendly. By producing alternative models, PLS regression may provide additional – and not alternative – ways of reading the data. Ideally, a comprehensive data analysis could include both ordinary and PLS regression and proceed from their results in order to get a better understanding of the phenomenon under examination. Furthermore, the computational complexity of PLS regression may stimulate interdisciplinary team-building, to the greater benefit of scientific research within the field of forest operations.

Costa, CRA ING, Monterotondo Scalo (Roma), Italy E-mail: cc@nn.it
Menesatti, CRA ING, Monterotondo Scalo (Roma), Italy E-mail: pm@nn.it
Spinelli, CNR IVALSA, Sesto Fiorentino (FI), Italy E-mail: spinelli@ivalsa.cnr.it

Click this link to register to Silva Fennica.

If you are a registered user, log in to save your selected articles for later access.

Contents alert

Your selected articles

Follow @SilvaFennica