Development of a New Technique for Safety Risk Assessment in Construction Projects Based on Fuzzy Analytic Hierarchy Process
Publication: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 7, Issue 3
Abstract
This study follows the fuzzy analytic hierarchy process to develop a semiquantitative technique to assess the safety risk of construction projects based on effective parameters affecting the probability and severity rates. Various studies targeting safety risk assessment in construction projects together with their research characteristics were investigated. In the second step, the initial structure of risk assessment was designed based on a semiquantitative technique of safety risk assessment. In the third step, a three-round Delphi method was employed, and an expert panel comprising 41 project managers and senior authorities of construction projects determined the existing components of the two factors of risk probability and severity. Finally, the weights of the components of risk probability and severity were determined so that their roles in determining the level of final risk could be specified. The normalized weights of probability and severity factors for calculating the semiquantitative safety were 0.48296 and 0.51704, respectively. Moreover, the incident probability factor included the four components of technical inspection, human reliability, incident learning, and hazard detection, with the following weights, respectively: 0.303, 0.364, 0.088, and 0.245. The incident severity factor included the four components of human injury, financial loss, operational interruption, and reputation damage, with the following weights, respectively: 0.369, 0.233, 0.191, and 0.207. The utilization of this technique can help reduce the risk of occupational incidents in construction projects.
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Data Availability Statement
All data, models, and codes generated or used during the study appear in the published article.
Acknowledgments
The authors are grateful to the head manager and all personnel for their participation in the implementation of the studied construction project. This work was supported by the Vice-Chancellor for Research and Technology of Qom University of Medical Sciences and Health Services under Grant No. 971000. Approval code: IR.MUQ.REC.138.030.
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ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 7 • Issue 3 • September 2021
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© 2021 American Society of Civil Engineers.
History
Received: Jan 29, 2021
Accepted: Apr 17, 2021
Published online: Jul 15, 2021
Published in print: Sep 1, 2021
Discussion open until: Dec 15, 2021
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