Current issue: 54(3)
The use of modern multi-functional forestry machines has already been associated with central nervous system fatigue induced by high mental workload. As these machines are being used under increasingly difficult terrain conditions, further knowledge is required on the expected aggravation of operators’ mental workload, so that suitable work/rest schedules can be developed. Within such a context, the aim of this study was to gauge aggravations of mental workload derived from increasing slope gradient. Measurements of eye activity were obtained from a representative harvester operator working in corridors with the following mean inclinations: 9%, 23% and 47%. The duration, frequency and trajectory of eye movements were used to determine the harvester operator’s mental workload, on the assumption that worsening work conditions would be reflected by increased eyeball activity. The number of fixations during the performance of all tasks increased with the increasing slope gradient. Similarly, fixation duration increased with slope gradient. The mean duration of saccades when working on a 23% slope was 5% shorter compared to work under a 9% gradient. A further significant shortening of saccade duration (~22%) occurred when working on a 47% slope. The good match between eye activity cycles and work cycles, visible especially on steep slopes, indicates that mental workload is related to work conditions. Overall, operating a forest harvester on steep slopes results in a greatly increased mental workload and calls for suitable rest schedules.
Industrial chipping is becoming increasingly popular, as the result of a growing demand for woody biomass. Industrial chippers are large, powerful machines that generate much noise and vibration. This study explored some factors that may affect exposure to noise and vibration, namely: feedstock type (branches vs. logs), work station characteristics (truck cab vs. separate cab) and knife wear (new knives vs. blunt knives). Exposure to noise was significantly affected by all three factors, and it was higher for branch feedstock, separate cabs and blunt knives. The higher exposure levels recorded for the separate cab were especially insidious, because they were below and above the hearing threshold and would elude immediate perception. Exposure to whole-body vibration (WBV) was significantly higher for branch feedstock and for the separate cab. Knife wear seemed to determine an increase in WBV, but this effect had no statistical significance and the result could not be taken as conclusive. Among the three factors studied, work station characteristics had the strongest effect. Further studies may extend the comparison to a wider range of options, as well as explore the use of exposure variation for machine diagnostics.
Speed and load sizes presented in three study reports on sulky skidding were compared with estimates based on ergonomic models. Speed and load size estimates were closely correlated with the observed values, when a 400 W energy expenditure of the subject was used. This corresponds to less than half of his submaximal oxygen intake and matches well with the heart rate given in one of the time studies. It seems possible to develop methods for evaluating the work pace/production rate for sulky skidding in varying terrain conditions.
The PDF includes an abstract in Finnish.
The concepts central to ergonomic research connected with the amount of strain caused by work was studied. A model was made to describe the process of strain. The model includes the following concepts: load or stress, human input, worker, strain, renewal of human resources, output and their hierarchical units. Based on the quality of human input, the forest work was roughly divided into two categories: (1) work demanding primarily muscle activity and (2) neuro-sensory work. In the first group, especially in cutting work, the main part of the human input is intensive consumption of muscle energy. In addition, work load causes accidents, wear of skeletal and muscular systems and processes by noise, vibrations, and climate. Correspondingly, when operating forest machines, the human input is mainly neuro-sensory functions of the central nervous system. Work load causes directly the effects of low frequency vibration and of other work conditions. The model was tested on data from research of forest work.
The PDF includes a summary in English.