Modelling and comparing timber winching performance in windthrow and uniform selective cuttings for two Romanian skidders

Published Date
December 2014, Volume 19, Issue 6, pp 473–482

Original Article

First Online: 

26 March 2014

DOI: 10.1007/s10310-014-0439-0

Cite this article as: 

Borz, S.A., Ignea, G. & Popa, B. J For Res (2014) 19: 473. doi:10.1007/s10310-014-0439-0

Author

• Stelian Alexandru BorzEmail author
• Gheorghe Ignea
• Bogdan Popa

Abstract

Cable skidders are one of the most used means for logging. In overall skidding operations, winching operations mark themselves out by consuming an important amount of time, which, depending on the work conditions can reach up to 43 % of the total skidding time. A better understanding of those conditions that may act as significant influence factors when estimating time consumption is needed as a prerequisite for better work organization. Based on an extensive time study, this paper demonstrates that along with influence factors that were already identified as being significant (especially winching distance), other influence factors, such as log volume, work pattern, felling area conditions and intervention type, slope, and winching direction, may prove significant in predicting time consumption for the main work elements of winching operations, as well as for a winching cycle. All the variables mentioned presented a great significance (p < 0.05) for a winching replication, and taken apart, they presented great significances for certain work elements. Distance was the most significant independent variable for all the realized time prediction models, slope and winching direction became relevant especially in the case of manual pulling of the cable, whereas intervention type and work patterns made the difference when performances were evaluated. The amount of data within data pools may have a great importance when trying to emphasize the relevance of different variables, as demonstrated by this paper.

References 

1. Behjou FK (2010) A techno-economic evaluation of skidding operation by Timberjack 450C and Clark Ranger 666DBS in Caspian forests. J Food Agric Environ 8(3–4):1020–1023Google Scholar
2. Behjou FK, Majnounian B, Namiranian M, Dvořák J (2008) Time study and skidding capacity of wheeled skidder Timberjack 450C in Caspian forests. J For Sci 54:183–188Google Scholar
3. Björheden R, Thompson MA (2000) An international nomenclature for forest work study. In: Field DB (ed) Proceedings of IUFRO 1995 S3.04 Subject area: 20th World Congress; Tampere, Finland. University of Maine, Orono, ME, pp 190–215
4. Demir M, Bilici E (2010) Assessment of timber harvesting mechanization level in Turkey. In: Proceedings of FORMEC 2010 conference: forest engineering: meeting the needs of the society and the environment, Padova, Italy, 11–14 July
5. Dinev D, Trichkov L (2010) Logging and realization of wood harvested in plantations of introducted forest tree species in Eastern Bulgaria. In: Proceedings of FORMEC 2010 conference: forest engineering: meeting the needs of the society and the environment, Padova, Italy, 11–14 July
6. Ghaffariyan MR, Naghdi R, Ghajar I, Nikooy M (2013) Time prediction models and cost evaluation of cut-to-length (CTL) harvesting method in a mountainous forest. Small Scale For 12:181–192CrossRefGoogle Scholar
7. Horvat D, Zečić Z, Šušnjar M (2007) Morphologial characteristics and productivity of skidder ECOTRACK 120 V. Croat J For Eng 28(1):11–25Google Scholar
8. Kluender R, Lortz D, McCoy W, Stokes B, Klepac J (1997) Productivity of rubber-tired skidder in southern pine forests. J For Prod 47(11–12):53–58Google Scholar
9. Kluender R, Lortz D, McCoy W, Stokes B, Klepac J (1998) Removal intensity and tree size effects on harvesting cost and profitability. For Prod J 48(1):54–59Google Scholar
10. Magagnotti N, Spinelli R (2012a) Replacing steel cable with synthetic rope to reduce operator workload during log winching operations. Small Scale For 11:223–236CrossRefGoogle Scholar
11. Magagnotti N, Spinelli R (eds) (2012b) COST Action FP0902 – good practice guideline for biomass production studies. CNR IVALSA, Florence, Italy, p 41. ISBN 978-88-901660-4-4. http://www.forestenergy.org
12. Mousavi R (2012) Effect of log length on productivity and cost of Timberjack 450C skidder in the Hyrcanian forest in Iran. J For Sci 58:473–482Google Scholar
13. Naghdi R, Mohammadi L (2009) Optimal forest road density based on skidding and road construction costs in Iranian Caspian forests. Casp J Environ Sci 7:79–86Google Scholar
14. Olsen E, Hossain M, Miller M (1998) Statistical comparison of methods used in harvesting work studies. Oregon State University, Forest Research Laboratory, Corvallis, OR. Research Contribution no 23, p 31
15. Oprea I (2008) Tehnologia exploatării lemnului, Transilvania University Press, Braşov
16. Özturk T (2010a) Productivity of New Holland farm tractor at beech stands on mountainous areas in Black Sea Region. For Ideas 16:52–57Google Scholar
17. Özturk T (2010b) Productivity of MB Track 900 tractor at beech stands on mountainous areas in Black Sea Region. Afr J Agric Res 5:28–33Google Scholar
18. Sabo A, Poršinsky T (2005) Skidding of fir roundwood by Timberjack 240C from selective forests of Gorski Kotar. Croat J For Eng 26:13–27Google Scholar
19. Sbera I (2007) Resursele de lemn şi potenţialul pieţei din România. Meridiane Forestiere 2:3–7Google Scholar
20. Spinelli R, Magagnotti N (2012) Wood extraction with farm tractor and sulky. Estimating productivity, cost and energy consumption. Small Scale For 11:73–85CrossRefGoogle Scholar
21. Spinelli R, Magagnotti N, Relano RL (2012) An alternative skidding technology to the current used crawler tractors in alpine logging operations. J Clean Prod 31:73–79CrossRefGoogle Scholar
22. Visser R, Spinelli R (2012) Determining the shape of the productivity function for mechanized felling and felling-processing. J For Res 17:397–402CrossRefGoogle Scholar
23. Vusić D, Šušnjar M, Marchi E, Spina R, Zečić Z, Picchio R (2013) Skidding operations in thinning and shelterwood cut of mixed stands––work productivity, energy inputs and emissions. Ecol Eng 61:216–223CrossRefGoogle Scholar
24. Wang J, Long C, McNeel J, Baumgras J (2004) Productivity and cost of manual felling and cable skidding in central Appalachian hardwood forests. For Prod J 54(12):45–51Google Scholar
25. Zar JH (1974) Biostatistical analysis. Prentice Hall Inc, Englewood CliffsGoogle Scholar
26. Zečić Z, Krpan APB, Vukušić S (2005) Productivity of C Holder 870 F tractor with double drum winch Ingland 4002 in thinning beech stands. Croat J For Eng 26:49–57Google Scholar

For further details log on website :
http://link.springer.com/article/10.1007/s10310-014-0450-5