Volume 8, Issue 3 (Summer 2019)                   J Occup Health Epidemiol 2019, 8(3): 148-155 | Back to browse issues page

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ElahiShirvan H, Zare S, Gharanjik E, Matin A, Bateni M, Hasanvand D et al . Risk assessment and identification of accident points at a highway construction site and drawing Safety Contour Maps (Southeastern Iran, 2019). J Occup Health Epidemiol 2019; 8 (3) :148-155
URL: http://johe.rums.ac.ir/article-1-356-en.html

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1- MSc in Occupational Health, Students’ Research Committee, Kerman University of Medical Sciences, Kerman, Iran.
2- Assistant Prof., Department of Occupational Health, School of Public Health, Kerman University of Medical Sciences, Kerman, Iran.
3- BSc in Occupational Health, School of Public Health, North Khorasan University of Medical Sciences, North Khorasan, Iran.
4- Associate Prof., Department of Occupational Health, Students’ Research Committee, Kerman University of Medical Sciences, Kerman, Iran. , ghotbi@kmu.ac.ir
Article history
Received: 2019/07/29
Accepted: 2019/10/13
ePublished: 2020/04/11
Abstract:   (2625 Views)
Background:The number of occupational safety incidents has been a major concern in terms of human, economic, and legal considerations. Risk assessment is a logical method for the assessment of risks, which specifies risks and their potential implications for individuals, materials, equipment, and the environment. This study aims to identify both risks and risk assessment methods at a highway construction site using the FMEA method and by drawing safety contour maps, making use of ArcGIS 10.2.
Materials and Methods: This study was conducted in 9 general steps, including 1. Reviewing demographic data, 2. Identifying human risks, 3. Identifying risk causes, 4. Identifying risk effects, 5. Determining the severity and occurrence of risks, 6. Rating risks, 7. Controlling risks, 8. Entering the coordinates and RPNs of occupations for each location in ArcGIS, and 9. Drawing safety contour maps using ArcGIS 10.2. The mean and standard deviation of the data were reported using SPSS Statistics V 22.0.
Results: At the site of this study, 62.97% of the units had moderate risks, and the rest had low risks (37.03%). The highest RPNs were for light machines and asphalt rollers with the values of 42.91 and 41.3, respectively. In contrast, the lowest RPNs were obtained for the laboratory and the water supply plant.
Conclusions: Most of the site units had moderate risks, so it is expected that the risk of the units would be minimized by implementing the recommendations.
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