Abstract
Forest operations are well known in exposing their workers to many risk factors, and they often require ergonomic interventions for improvement. In this regard, evaluation of biomechanical exposure has gained a lot of interest due to the concerning scientific results repeatedly showing the association between poor working postures and the development of work-related musculoskeletal disorders. Due to its simplicity, easy understanding, cost affordability, and the capability to evaluate the whole body, the OWAS method has been commonly used in postural evaluation of forestry work, being able to map the experimental observations in a final action category, in the form of a postural risk index (PRI), which helps designing or taking actions for ergonomic improvement. However, postural comparability is both relevant and important when, for instance, one tries to improve a work method or to introduce a new technology. Unfortunately, the PRI metric holds a rather low capability to characterize the changes brought by such factors in terms of postural dissimilarity or similarity, making it difficult to accurately follow the changes. For this reason, we introduce in the postural analysis, test and discuss herein two commonly used similarity metrics as specific to plant sociology and other ecology-related sciences, namely the Sørensen’s quotient of similarity (hereafter QS) and the Canberra metric (hereafter CM); their selection was based on their mathematical capabilities of dealing with data at two resolutions, namely species and individuals. Three case studies were setup to show the differences between QS, CM, and PRI and their usefulness for postural analysis while, for a better understanding, the results were described and discussed by analogy to the living world. As the technology of automating data collection and processing for postural analysis is in progress, the utility of similarity metrics in postural assessment and comparison could be further expanded so as to map a given work sequence in the time domain against best-fit postural profiles. The main conclusion of this study is that the PRI is useful for action-taking while the similarity metrics are useful for pairwise postural change evaluations and comparison.
Highlights
Wood procurement is a complex process that includes a set of operations of which many are implemented outdoors, in workplaces that are often characterized by difficult terrain and adverse weather conditions [1]
The Ovako Working Posture Analysis System (OWAS) is an observational postural assessment method developed on the basis of three main principles such as the simplicity in learning and use, unambiguity in the interpretation of results, and possibility of formulating improvements in terms of postures by considering factors such as the health and safety, with the main emphasis on the discomfort caused by working postures [56]; it was developed and tested initially in the steel industry of Finland with the aim of correcting poor postures and it was based on work sampling as a method to collect the data needed in evaluations [56]
The stepwise procedure used to exclude the data from sample B from top to bottom (TTB) and from the bottom to the top (BTT) of the list, which ordered the species numerically according to their belonging to action categories, has resulted in postural risk indexes which increased from
Summary
Wood procurement is a complex process that includes a set of operations of which many are implemented outdoors, in workplaces that are often characterized by difficult terrain and adverse weather conditions [1]. A significant body of knowledge has been built by applying the ergonomics methods to forest operations, by studies spanning a wide variety of topics and a fairly large number of operational setups and harvesting equipment [11] Such studies have evaluated the workload and work difficulty by the means of cardiovascular response [12,13,14,15,16,17,18,19,20,21,22,23], mental workload [24,25], exposure to harmful factors caused by the use of tools and machines such as noise and vibrations [21,23,26,27,28,29,30,31,32,33,34], effects of environmental parameters on the performance of work [35], accidents, exposure to risks and safety issues [36,37,38,39,40,41,42] and last, but not least, the working postures [21,43,44,45,46]
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