Automatic Time Study Method for Recording Work Phase Times of Timber Harvesting
Abstract:The objective of the present study was to develop an automatic time study method based on a process-data model for single-grip harvesters, with inputs based on data automatically collected by the harvester's onboard computer. The method integrates the phases of the work cycle into components under conditions in which the work phases may overlap to varying degrees. During the work phase analysis, we found that process-data models differed under similar work conditions because work phases could not be completely separated during the automatic recording of data. We therefore used the combined data provided by manual and automatic timing to develop a new process-data model for a single-grip harvester's work. We also analyzed the overlapping and simultaneous work phases to optimize the improved process-data model. The results were satisfactory, and the method can be systematically used in time studies based on automatically recorded data by modifying the process-data model using the approach described in this article. Adjustment of the model to improve data-recording accuracy compared with manual time studies has great potential, but this must be confirmed through additional harvesting experiments during work studies with different machines and in different forests.
Document Type: Research Article
Publication date: August 21, 2013
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- Forest Science is a peer-reviewed journal publishing fundamental and applied research that explores all aspects of natural and social sciences as they apply to the function and management of the forested ecosystems of the world. Topics include silviculture, forest management, biometrics, economics, entomology & pathology, fire & fuels management, forest ecology, genetics & tree improvement, geospatial technologies, harvesting & utilization, landscape ecology, operations research, forest policy, physiology, recreation, social sciences, soils & hydrology, and wildlife management.
Forest Science is published bimonthly in February, April, June, August, October, and December.
2015 Impact Factor: 1.702
Ranking: 16 of 66 in forestry
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