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Updated: Aug 2, 2025

Design and Analysis for Fall Detection System Simplification
Published on: April 6, 2020
Occupational safety risk analysis in construction sites based on fuzzy analytic hierarchy process: A case study in a
Ahmad Soltanzadeh1, Mohsen Mahdinia1, Ehsan Jafarinia2
1Research Center for Environmental Pollutants, Department of Occupational Health and Safety Engineering, Faculty of Health, Qom University of Medical Sciences, Qom, Iran.
Background:
Construction projects are one of the most critical occupational sectors that experienced many challenges in occupational accidents and safety performance.
Objective:
This study was designed to assess safety risk in construction projects based on fuzzy analytic hierarchy process.
Methods:
This study was conducted with 12 construction and occupational safety experts in one of the largest construction projects in Tehran-Iran in 2020. The process of this study included (1) risk identification, (2) measurement of risk parameters and sub-parameters, and (3) risk assessment based on a fuzzy analytic hierarchy process. Risk-forming parameters in this study included the probability and severity of the event. The probability of occurrence was estimated based on four sub-parameters of technical inspection, accident experience, detection probability, and human reliability. Sub-parameters of severity included human injury, cost imposition, tarnishing the organization's esteem, and impact on project timing and work stoppage.
Results:
Twenty-eight identified hazards were examined in the studied construction project, including falling from a height (9-hazard), falling objects (2-hazard), electric shock (6-hazard), falling crane or load (6-hazard), elevator crashes (2-hazard), and soil fall (3-hazard). Safety risk assessment revealed that 27 risk sources were at the tolerable level and one risk source was unacceptable.
Conclusion:
This study demonstrated that the risk levels in the studied construction project were tolerable and unacceptable. The obtained model in this study demonstrated that using parameters that determine the probability and severity of risk according to the nature of the working environments can be a practical step in risk evaluating and implementing control measures.
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