Articles containing the keyword 'learning curve'
Category : Research note
The forwarder loads processed wood and transports it to a landing. Productivity of forwarding could be improved by increasing driving speed, but difficult forest terrain limits this. According to current literature, crane work is the most time-consuming work element of forwarding, so improving crane work productivity is essential for improving forwarding productivity. One way to do this is through automation of recurrent boom movement patterns, or alternatively automation can be used to ease crane work. When using conventional boom control (CBC), the operator manually controls each of the independent boom joint movements and combines them to achieve a desired boom tip movement, but boom tip control (BTC) allows the operator to control boom tip movements directly. The objective of the present study was to examine whether BTC facilitates crane work and affects the slopes of learning curves for beginner-level forwarder operators. The study was carried out using a standardised test routine to evaluate effects of two fixed factors, system (levels: CBC, BTC) and point of time (four levels), on five dependent variables. Four of the five dependent variables measured ease of boom control and the fifth measured crane work productivity. The results showed that there were no significant differences in the slopes of learning curves between the systems but the BTC did increase crane work productivity and made boom control easier.
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Manner,
The Forestry Research Institute of Sweden (Skogforsk), Uppsala Science Park, SE-751 83 Uppsala, Sweden
http://orcid.org/0000-0002-4982-3855
E-mail:
jussi.manner@skogforsk.se
- Gelin, The Forestry Research Institute of Sweden (Skogforsk), Uppsala Science Park, SE-751 83 Uppsala, Sweden E-mail: olle.gelin@skogforsk.se
- Mörk, The Forestry Research Institute of Sweden (Skogforsk), Uppsala Science Park, SE-751 83 Uppsala, Sweden E-mail: anders.mork@skogforsk.se
- Englund, The Forestry Research Institute of Sweden (Skogforsk), Uppsala Science Park, SE-751 83 Uppsala, Sweden E-mail: martin.englund@skogforsk.se
