Volume 8, Issue 2 (Summer 2021)
johe 2021, 8(2): 24-31 |
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Mirmohammadsadeghi A, Abniki H, Hasanpour H. Risk Management Modeling for HazMat Transportation. johe 2021; 8 (2) :24-31
URL: http://johe.umsha.ac.ir/article-1-675-en.html
URL: http://johe.umsha.ac.ir/article-1-675-en.html
1- Department of Industrial Engineering, Faculty of Engineering, University of Imam Hussein , ammsadeghi@ihu.ac.ir
2- Department of Industrial Engineering, Faculty of Engineering, University of Imam Hussein
2- Department of Industrial Engineering, Faculty of Engineering, University of Imam Hussein
Abstract: (2604 Views)
Background and Objective: Industrial development accelerates the transportation of hazardous materials, especially in developing countries, which leads to an increased risk of accidents. Consequently, conducting further research is essential to reduce these consequences. The present study aimed to provide a simple, comprehensive and innovative model of risk management for transporting hazardous materials.
Materials and Methods: The proposed model consisted of four steps of identification, analysis, evaluation, and control. Appropriate layouts and tools such as system dynamics and fuzzy AHP were used to ensure that all relevant elements were carefully examined. The model was implemented in a real example of hydrazine explosive transport.
Results: In the risk analysis stage, it was found that population density is the most important factor in increasing the risk of transporting hazardous materials along with sub-criteria related to driver and management. Finally, ways to reduce risk to an acceptable level were examined during the presentation of risk control planning.
Conclusion: Using system dynamics in the risk identification stage and fuzzy AHP in the risk analysis stage along with expert judgment can be effective in improving the risk management process.
Materials and Methods: The proposed model consisted of four steps of identification, analysis, evaluation, and control. Appropriate layouts and tools such as system dynamics and fuzzy AHP were used to ensure that all relevant elements were carefully examined. The model was implemented in a real example of hydrazine explosive transport.
Results: In the risk analysis stage, it was found that population density is the most important factor in increasing the risk of transporting hazardous materials along with sub-criteria related to driver and management. Finally, ways to reduce risk to an acceptable level were examined during the presentation of risk control planning.
Conclusion: Using system dynamics in the risk identification stage and fuzzy AHP in the risk analysis stage along with expert judgment can be effective in improving the risk management process.
Type of Study: Research Article |
Subject:
Safety
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