Sammanfattning

Factors affecting forwarding work are interesting because they can be used to better optimize forwarding routes and to predict costs. The main objective of this study was to investigate the association between driving speed and driving distance when forwarding. Data was automatically collected during 2.5 years from two large forwarders operating during final felling in central Sweden. Driving speeds for the work tasks Driving unloaded, Loading drive and Driving loaded were analysed using correlation, least-squares regression, and quantile regression. The results showed that speed and distance were strongly correlated for the work element Driving unloaded, while the correlation was weaker for Loading drive and Driving loaded. Possible factors leading to these results are as follows: longer travelling distances stimulate better planning and the establishment of better extraction roads; operators may feel stressed and drive faster as travelling distance increases; and finally, the relative influence of accelerations and decelerations decreases with increasing driving distance. Also, the use of quantile regression was successful and provided information that normal least-squares regression does not provide.

Nyckelord

cut-to-length; quantile regression; automatic data collection; forwarder; logging; big data

Publicerad i

Journal of Forest Science
2019, Volym: 65, nummer: 5, sidor: 183-194

SLU författare

• Berg, Simon

  • Institutionen för skogens biomaterial och teknologi, Sveriges lantbruksuniversitet
    

• Ersson, Back Tomas

  • Skogsmästarskolan, Sveriges lantbruksuniversitet
    

Globala målen

SDG9 Bygga motståndskraftig infrastruktur, verka för en inkluderande och hållbar industrialisering samt främja innovation


UKÄ forskningsämne

Skogsvetenskap


Publikationens identifierare

DOI: https://doi.org/10.17221/23/2019-JFS

Permanent länk till denna sida (URI)

https://res.slu.se/id/publ/101571