Abstract
t Integration of technology is commonplace in forestry equipment supporting higher levels of automation and efficiency. For technology adoption to be successful it must demonstrate improvement in productivity, cost–effectiveness or in human factors and ergonomics. Cable yarding lends itself to automation with repetitive machine movement along a fixed corridor, as established by the skyline. This study aimed at investigating the difference in productivity between the two possible settings (manual and automated) of a Valentini V850 yarder equipped with automatic path programming, with a Bergwald 3-t carriage and radio controlled chokers. The study took place in the northern Italian Alpine eastern region over a period of 8 days on two separate corridors, resulting in 280 measured cycles split between manual and automated. Results in terms of absolute numbers were very close for the two system options, but significant differences were found. For example, inhaul time was longer, but outhaul time shorter for the automated system. Productivity ranged from 8.2 to 13.3 m3 PMH-1, and cost from approximately 20 to 30 € m-3. The automated system did achieve a significantly higher productivity, but differences declined with extraction distance. When that was combined with the slightly higher cost for the automated system, the automated system was more cost-effective on extraction distances less than 200 m, and the manual system on longer distances.
Highlights
Over the past decade, forest technology has made significant progress in order to support a dynamic industry that sets urgent demands for new equipment and techniques (Thor 2014, Müller et al 2019)
Harvester operators experience a very high mental workload and they can quickly fatigue (Spinelli et al 2020) and forwarder operators may spend lots of time driving over the same trails, which will lead to monotony and boredom (Grzywiński & Hołota 2006)
Mean payload was approximately 1.5 m3, with no significant differences between treatments or lines (Table 2)
Summary
Forest technology has made significant progress in order to support a dynamic industry that sets urgent demands for new equipment and techniques (Thor 2014, Müller et al 2019). Within the specific field of forest operations, most new developments have aimed at increasing productivity and reducing labor input and risk exposure which have been the main objectives of forest mechanization for decades (Heinimann 2007). The data collected during harvesting can be integrated with geospatial information to optimize machine performance, leading to precision forestry (Mousazadeh 2013). New technology such as intelligent boom control makes it easier for beginners to learn how to efficiently operate their machines and leads to achieving high productivity within a short learning time (Löfgren 2009, Manner et al 2017). A higher degree of machine autonomy could mitigate operator workload and improve safety, health and general wellbeing - besides offering productivity gains that can be sustained in the long run (Cottrel & Barton 2013, Visser & Obi 2019)
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