Assessment and Comparison of Machine Operators’ Working Posture in Forest logging

Document Type : Complete scientific research article

Authors

1 Ph.D. Student of Forest Science and Engineering, Faculty of Natural Resources, University of Guilan, Sowmeh Sara, Iran

2 Professor, Dept. of Forest Science and Engineering, Faculty of Natural Resources, University of Guilan, Sowmeh Sara, Iran

3 Professor, Dept. of Forest Science and Engineering, Faculty of Natural Resources, University of Guilan, Sowmeh Sara, Iran.

4 Associate Prof., Dept. of Occupational Health, School of Health, Guilan University of Medical Sciences, Rasht, I. R. Iran.

5 Assistant Prof., Lab of Forest Utilization, Faculty of Forestry and Natural Environment, Aristotle University of Thessaloniki, POB 227, Thessaloniki, Greece.

Abstract

Background and Objectives:
Although the mechanization of timber harvesting reduces costs and increases productivity, it exposes machine operators to musculoskeletal disorders (MSDs) resulting from awkward working postures, prolonged sitting, and whole-body vibration. MSDs are among the most significant occupational health problems affecting forest machine operators and may lead to decreased productivity, work delays, and increased healthcare costs. Given the lack of comprehensive research in Iran on the assessment of working postures among logging machine operators, this study aimed to evaluate and compare the working postures of operators of two logging machines—the Timberjack 450C rubber-tired skidder and the ITM 285 agricultural tractor—in plantation forests of western Guilan Province, Iran.
Materials and Methods:
This cross-sectional observational study was conducted during the summer of 2024. Logging operations with the rubber-tired skidder were performed in Compartment 12 of Pilambra Forest, while tractor data were collected from Compartment 5 of Haft-Daghanan District. Operators’ working postures during different operational phases—including travel unloaded, maneuvering, winching, travel loaded, unloading, and sorting and piling (for the skidder), and travel unloaded, load collection, travel loaded, and unloading (for the tractor)—were recorded using video cameras. Postures were evaluated using the snapshot sampling method and the Ovako Working Posture Analysis System (OWAS). A total of 2,652 images were analyzed for the skidder and 5,539 images for the tractor. The Postural Risk Index (PRI) was calculated based on the frequency distribution of postures across action categories.
Results:
For both machines, the highest proportion of working postures was classified at Action Level 2, accounting for 67.08% for the skidder and 73.06% for the tractor. Action Level 1 comprised 32.67% for the skidder and 24.68% for the tractor. Action Level 3 represented 0.15% for the skidder and 2.26% for the tractor, while no postures were classified at Action Level 4 for either machine. The PRI was 167 for the skidder and 177 for the tractor, indicating a higher postural risk for the tractor operator. The skidder operator adopted 9 distinct working postures, whereas the tractor operator adopted 12. In skidder operations, posture codes 2111 (1,360 observations) and 3111 (762 observations) were the most frequent. For the tractor, posture code 2111 was the most frequent across operational phases (3,577 observations).
Conclusion:
Although both machines presented moderate postural risk levels, the specialized cabin design of the skidder, stable seated posture, and ergonomic control layout contributed to more favorable working postures and a lower PRI. In contrast, the agricultural tractor—due to its non-specialized design, absence of a standard cabin, and frequent transitions between seated and standing positions—was associated with greater postural variability and higher risk. Implementing preventive measures such as scheduled rest breaks, stretching exercises, ergonomic training, improved seat design, and reduced continuous working time is recommended to mitigate musculoskeletal disorders.

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Main Subjects

References

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Journal of Wood and Forest Science and Technology
Volume 33, Issue 1
March 2026
Pages 91-109

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