Time and motion studies of forest harvesting machines are an important component of forest operations research. The trouble is that traditional manual methods require a skilled observer, are time consuming, limited in duration and potentially hazardous. Few automated techniques to date have had the breadth and ease of application to conduct long term autonomous studies.
Researchers from the University of the Sunshine Coast set out to determine whether a fully automated time study system could be created to analyse GPS and vibration sensor data from a forwarder to accurately estimate the forwarder total cycle time and the type and duration of individual time elements.
When compared with traditional time and motion studies for three forwarders at different sites, the automated system accurately logged each work cycle start and end points. The system, however, had some issues in correctly labelling events where the forwarder slowed to negotiate steep areas.
These errors may be able to be addressed by adding further rules to the automated system.
Click here for source (Croatian Journal of Forest Engineering)
Photo: Wikimedia
