Factors affecting forwarder productivity

Abstract

Modern forwarders are an effective extraction option for timber harvesting operations that provide the opportunity for higher levels of mechanization. With their ability to carry logs from the forest to the roadside or processing areas, they have an established lower environmental impact in comparison to tree-length skidding options. However, little is published regarding their productivity potential or the factors that influence productivity. Three case studies were carried out; (1) a selective harvest in Calabria, Italy, with a smaller 12 t capacity John Deere 1110E, (2) a clear-cut on the West Coast of New Zealand, with a larger 19 t capacity John Deere 1910E and (3) a larger clear-cut operation in Canterbury, New Zealand, with two John Deere 1910E forwarders. An elemental time and motion study was used resulting in 73.4 h of detailed data, with 159 cycles extracting 2241 m³ of timber. Productivity models were created for all three sites as well as one combined model. Average cycle time was 33.2, 24.2 and 22.8 min, and average productivity 24.6, 37.1 and 42.7 t per productive machine hour, respectively. Cycle time was the fastest, and consequently productivity the highest, at the Canterbury site where the terrain roughness was low, overcoming any effect of the average small piece size (0.59 m³). Travel speed was slowest at the West Coast site showing the effect of wet and difficult terrain, with travel empty speed being just 3.8 km/h, compared to 6.7 and 6.9 km/h at the other two sites. Productivity at the two clear-cut operations was significantly higher than the selective cut, compounded by the use of the larger capacity forwarders. Distance and payload were significant factors for each cycle time model; in the combined model the sites were also significant. The calculated unit cost of forwarder extraction in the sites ranged from €2.55 to €4.70/m³. For regions such as southern Italy that have relatively low levels of forest mechanization, this information can be used to help design and improve more traditional labor-intensive harvesting systems.

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