Safety risk management is one of the important techniques to be performed in large construction projects. The purpose of risk management is to identify the origin of the risks, uncertainties, and effects then offer suitable management responses to these risks. In this research, first, the possible accident in construction projects was identified by studying various sources and statistics in Iran. Brainstorm was used to specify the determinant factors in these accidents. Fault tree analysis and fuzzy logic were employed to evaluate these accidents and calculate their probability of occurrence. Next, the significance of each determinant factor in the accident was identified using the improvement index in fault tree analysis. Finally, the determinant factors in the accident were prioritized in terms of significance to provide a proper solution. The mentioned steps were carried out in two commercial building projects located south of Tehran, Iran. The most important safety risks were determined to be the fall of materials from the height with a probability of 92% in project A, and the fall of workers from the height with a probability of 52% in construction project B. Also, the second important risk in both projects was the fall of objects with a probability of 91% of construction project A and 51% for project B. The most important determinant factors were the insufficient skill of the workers in project A (with an improving safety index of 14.4%) and insufficient light and visibility in project B (with an improving safety index of 9%). The use of the Likert scale in the questionnaire instead of the Thurston scale and applying improvement index of fault tree in prioritization may be new compared to other studies.
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Aghaei, P., Asadollahfardi, G. & Katabi, A. Safety risk assessment in shopping center construction projects using Fuzzy Fault Tree Analysis method. Qual Quant (2021). https://doi.org/10.1007/s11135-021-01115-9
- Safety in the construction industry
- The combination of fuzzy logic and fault tree
- Risk assessment