Ergonomic assessment and validation are important in designing sustainable forest operations. Measurement and grading play a central role in the wood supply chain and updated solutions have started to emerge for such activities. Procuring biometric data by mobile scanning platforms has been shown to have a high potential in replacing traditional wood measurement methods, but no assessments were carried out to see if these solutions are sustainable from an ergonomics point of view. Based on more than 63 k still images, this study evaluates the working postures of three measurement options, namely, traditional measurement, scanning by a smartphone, and scanning by a commercial laser scanner. The OWAS method was used as an assessment framework to compute the postural risk indexes. A correspondence analysis was implemented to explore the association between the studied work tasks and severity of exposure, and the postural similarity of tasks was evaluated by the Canberra metric. The use of digital measurement solutions seems to be better from a postural point of view since their risk indexes were well below 200. In contrast, traditional wood measurement tasks produced postural risk indexes that were close to 250. By considering the body components, digital measurement solutions seemed to indicate a distinct postural profile. Moreover, the digital solutions stood well apart in the range of the first two action categories, indicating no urgent need for postural improvement, which was not the case for manual measurements. The main conclusion of the study is that state-of-the-art digital solutions are better from a postural point of view. For full validation, population-level studies should be carried out.

Postural Assessment of Three Wood Measurement Options by the OWAS Method: Digital Solutions Seem to Be Better / Borz, S. A.; Papandrea, S. F.; Marcu, M. V.; Bacenetti, J.; Proto, A. R.. - In: FORESTS. - ISSN 1999-4907. - 13:12(2022), p. 2007. [10.3390/f13122007]

Postural Assessment of Three Wood Measurement Options by the OWAS Method: Digital Solutions Seem to Be Better

Papandrea S. F.
;
Proto A. R.
2022-01-01

Abstract

Ergonomic assessment and validation are important in designing sustainable forest operations. Measurement and grading play a central role in the wood supply chain and updated solutions have started to emerge for such activities. Procuring biometric data by mobile scanning platforms has been shown to have a high potential in replacing traditional wood measurement methods, but no assessments were carried out to see if these solutions are sustainable from an ergonomics point of view. Based on more than 63 k still images, this study evaluates the working postures of three measurement options, namely, traditional measurement, scanning by a smartphone, and scanning by a commercial laser scanner. The OWAS method was used as an assessment framework to compute the postural risk indexes. A correspondence analysis was implemented to explore the association between the studied work tasks and severity of exposure, and the postural similarity of tasks was evaluated by the Canberra metric. The use of digital measurement solutions seems to be better from a postural point of view since their risk indexes were well below 200. In contrast, traditional wood measurement tasks produced postural risk indexes that were close to 250. By considering the body components, digital measurement solutions seemed to indicate a distinct postural profile. Moreover, the digital solutions stood well apart in the range of the first two action categories, indicating no urgent need for postural improvement, which was not the case for manual measurements. The main conclusion of the study is that state-of-the-art digital solutions are better from a postural point of view. For full validation, population-level studies should be carried out.
2022
digitalization
ergonomics
postural analysis
risk
scanning
sorting
wood measurement
wood supply chain
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12318/131976
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