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Simulation-based comparison between two crane-bunk systems for loading work when considering energy-optimal motion planning
Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics.
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2019 (English)In: International Journal of Forest Engineering, ISSN 1494-2119, E-ISSN 1913-2220Article in journal (Refereed) Epub ahead of print
Abstract [en]

Performing work for extended periods of time while using the lowest amount of resources is an important aspect for productivity in many industries. In forestry, the productivity of a forwarder is seen as the volume of material it can extract to a roadside landing in a certain amount of time, where the process of loading and unloading logs represents a large part of the work. During this process, the esnergy consumed by the machine is directly related to the speed of the crane. Thus, increasing productivity implies increasing the operating velocity of cranes. But according to current design of forestry cranes, this conversely leads to an undesired increase in consumption of resources (e.g. fuel). A second method is to alter the machine's design, such as rotating the log bunk. This article considers both methods through a simulation-based comparison aiming to evaluate the energy consumption of two crane-bunk systems when loading. The first simulation system considers a forestry crane with a fixed log bunk (forwarder-like crane). The second simulation system takes into account a forestry crane and a rotating log bunk (harwarder-like crane). The analysis presented considers the fundamental mathematics required to analyze the dynamics of forestry cranes and the principles required to plan energy-optimal motions. The simulation results show that energy savings of 43% to 61% can be obtained by determining energy-optimal motions and using a harwarder-like crane architecture.

Place, publisher, year, edition, pages
TAYLOR & FRANCIS INC , 2019.
Keywords [en]
Log loading, harwarder, forwarder, motion planning, virtual holonomic constraints
National Category
Robotics
Identifiers
URN: urn:nbn:se:umu:diva-164538DOI: 10.1080/14942119.2019.1653027ISI: 000483783200001OAI: oai:DiVA.org:umu-164538DiVA, id: diva2:1370266
Available from: 2019-11-14 Created: 2019-11-14 Last updated: 2019-11-14

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Lindroos, Ola
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