Speaker
Description
The use of the cut-to-length method as a wood harvesting system creates a demanding operating environment for harvester operators, especially in the Nordics. In addition to the harvesting method itself, high productivity demands and environmental conditions such as terrain, weather, vibration and cabin tilting increase the demands of the operator’s work. This environment places mental, physical, and cognitive strain on the operator, making the work holistically challenging. The workload of harvester operators can be reduced through various operator assistance systems. Currently, harvesters are already equipped with some assistance systems such as boom-tip control, automated bucking system, a reversing camera, and GPS positioning and maps. These systems support the operator’s decision-making and machine control. In the future, operator assistance systems will increasingly utilize forest machine data produced by various sensors, reducing unnecessary tasks and workload for the operator.
The objectives of this study were to determine what kinds of operator assistance systems will be needed in the future, how information provided by these systems should be presented, and what types of support operators require in their work. In addition, the study examined which assistance systems and advance information harvester operators currently use and how they receive feedback on their work. The interviews included 50 harvester operators across Finland and were semi‑structured, incorporating a two‑step Likert scale, with additional open‑ended questions added to complement and deepen the information obtained from the Likert‑scale items. The two‑step Likert scale was adapted from the Importance–Performance Analysis approach and analysed within this framework, enabling a combined assessment of how important each factor is to operators and how well it currently performs.
According to the results, harvester operators wish for assistance systems to support controlling thinning intensity, reporting harvest quality, and identifying tree characteristics and quality. These systems rely on data collected by mobile LiDAR scanners, which capture precise 3D measurements of the forest stand and make it possible to automatically identify tree attributes relevant to thinning and quality assessment. Operators were generally satisfied with the current method of presenting information on a traditional computer display, but they also expressed interest in new presentation methods such as AR‑glasses and head‑up display (HUD) systems. Among the existing assistance systems, GPS positioning and maps were considered the most essential. Boom-tip control was also regarded as useful, although operators felt that the system still requires further development. Receiving advance information about legally protected forest nature sites, buffer zones around water systems, and roadside landing areas was considered particularly important. In addition, based on the interviews, operators expressed a desire to receive regular monthly feedback on their work.
This study provides new, up‑to‑date insights into the needs of harvester operators regarding the development of operator assistance systems, thereby supporting the future development of forest machines in collaboration with manufacturers, contractors, operators, and researchers.
| Keywords | harvester; CTL; decision-support; ergonomics |
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