The OWAS Method. Preliminary Results For the Evaluation of the Risk of Work-related Musculo Skeletrical Disorders (WMSD) in the Forestry Sector in Italy. The article examines the OWAS method (Ovako Working-postures Analysis System) and its use for the evaluation of the risk of WMSD. In particular, a derived application has been validated in some case studies concerning forest harvesting both in mountain environment (silvicultural interventions in coniferous stands) and in flatland yards (final cut in poplar plantations). The variant of the method allows to attribute a specific class of risk to the postures assumed during the job and to calculate the relevant index of risk on the bases of the time frequency (by a multi-moment time study). The above index is expressed as a weighted value that ranges from 100 to 400 and the value obtained corresponds to a proportional level of risk and a consequent interventions to be implemented. Yards related to harvesting in coniferous stand have highlight an higher level of risk compared to those of poplar, with an average value of the OWAS index that respectively reached 191 and 140. In the first case the more critical operational phase was the on-site processing, while the slope and the morphology of the site have considerably influenced the assumption of inadequate postures by workers. In the yards of poplar the phases connected to the mayor risk were instead the falling operation followed by the logs measurement. The application of the OWAS method as it is proposed in this study, enables to acquire both ergonomic and yield information and to asses data in terms of working activity, job phase or single operator. It appears therefore a valid tool for the evaluation of the examined risk and could be usefully diffuse, like already happens in other countries, as an alternative or as a mean of comparison to other reference methods that register some problems of application in the forestry activities.
Il metodo OWAS. Prime applicazioni nella valutazione del rischio di patologie muscolo-scheletriche nel settore forestale in Italia
ZANUTTINI, Roberto;
2005-01-01
Abstract
The OWAS Method. Preliminary Results For the Evaluation of the Risk of Work-related Musculo Skeletrical Disorders (WMSD) in the Forestry Sector in Italy. The article examines the OWAS method (Ovako Working-postures Analysis System) and its use for the evaluation of the risk of WMSD. In particular, a derived application has been validated in some case studies concerning forest harvesting both in mountain environment (silvicultural interventions in coniferous stands) and in flatland yards (final cut in poplar plantations). The variant of the method allows to attribute a specific class of risk to the postures assumed during the job and to calculate the relevant index of risk on the bases of the time frequency (by a multi-moment time study). The above index is expressed as a weighted value that ranges from 100 to 400 and the value obtained corresponds to a proportional level of risk and a consequent interventions to be implemented. Yards related to harvesting in coniferous stand have highlight an higher level of risk compared to those of poplar, with an average value of the OWAS index that respectively reached 191 and 140. In the first case the more critical operational phase was the on-site processing, while the slope and the morphology of the site have considerably influenced the assumption of inadequate postures by workers. In the yards of poplar the phases connected to the mayor risk were instead the falling operation followed by the logs measurement. The application of the OWAS method as it is proposed in this study, enables to acquire both ergonomic and yield information and to asses data in terms of working activity, job phase or single operator. It appears therefore a valid tool for the evaluation of the examined risk and could be usefully diffuse, like already happens in other countries, as an alternative or as a mean of comparison to other reference methods that register some problems of application in the forestry activities.File | Dimensione | Formato | |
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