Journal article
Time Prediction Models and Cost Evaluation of Cut-To-Length (CTL) Harvesting Method in a Mountainous Forest
Small-scale Forestry, Vol.12(2), pp.181-192
2013
Abstract
Time equations are derived for felling with chainsaw, skidding with cable wheeled skidder, loading with grapple hydraulic loader and trucking of logs within a cut-to-length harvesting method. The continuous time study method was applied to collect data for felling, skidding, loading and a transportation model. Multiple regression analysis via SPSS software was applied to develop the time models. Felling time was found to be highly dependent on diameter at breast height. Skidding distance, winching distance, slope of the trail and piece volume were significant variables for the skidding time prediction model. The loading time model was developed considering piece volume. Transportation distance and load volume were used as independent variables in modeling the transportation time. The net production of felling was estimated at 12 trees/h (56.65 m3/h). The net production rates for skidding, loading and traveling averaged 18.51, 41.90 and 3.32 m3/h respectively. The total cost of harvesting from stand to mill was estimated 19.70 €/m3. The skidding phase was the most expensive component of the cut-to-length method. The bucking and delimbing components were less costly than the other logging phases. The results of this study can be used for harvesting planning and productivity optimization.
Details
- Title
- Time Prediction Models and Cost Evaluation of Cut-To-Length (CTL) Harvesting Method in a Mountainous Forest
- Authors
- Mohammad R Ghaffariyan (Author) - University of TasmaniaRamin Naghdi (Author) - University of Guilan, IranIsmael Ghajar (Author) - Tarbiat Modares University, IranMehrdad Nikooy (Author) - University of Guilan, Iran
- Publication details
- Small-scale Forestry, Vol.12(2), pp.181-192
- Publisher
- Springer Netherlands
- Date published
- 2013
- DOI
- 10.1007/s11842-012-9204-4
- ISSN
- 1873-7617
- Organisation Unit
- University of the Sunshine Coast, Queensland; Forest Industries Research Centre; Forest Research Institute
- Language
- English
- Record Identifier
- 99450068002621
- Output Type
- Journal article
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