Volume 4, Issue 3 (9-2014)                   J Health Saf Work 2014, 4(3): 67-74 | Back to browse issues page

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Abootorabi S M, Mehrno H, Omidvari M. Proposing a model for safety risk assessment in the construction industry using gray multi-criterion decision-making. J Health Saf Work 2014; 4 (3) :67-74
URL: http://jhsw.tums.ac.ir/article-1-5180-en.html
1- Bsc. Industrial Engineering, Department of Industrial Engineering, Islamic Azad University of Qazvin
2- Instructor of Department of Industrial Engineering, Faculty of Mechanical and Industrial Engineering, Islamic Azad University of Qazvin , mehrno20@yahoo.com
3- Assistant Professor of Department of Industrial Engineering, Faculty of Mechanical and Industrial Engineering, Islamic Azad University of Qazvin
Abstract:   (10410 Views)

Introduction: Statistical Report of the Social Security Organization indicate that among the various industries, the construction industry has the highest number of work-related accidents so that in addition to frequency, it has high intensity, as well. On the other hand, a large number of human resources are working in this whish shows they necessity for paying special attention to these workers. Therefore, risk assessment of the safety in the construction industry is an effective step in this regard. In this study, a method for ranking safety risks in conditions of low number of samples and uncertainty is presented, using gray multi-criterion decision-making.

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Material and Method: In this study, we first identified the factors affecting the occurrence of hazards in the construction industry. Then, appropriate for ranking the risks were determined and the problem was defined as a multi-criterion decision-making. In order to weight the criteria and to evaluate alternatives based on each criterion, gray numbers were used. In the last stage, the problem was solved using the gray possibility degree.

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Results: The results show that the method of gray multi-criterion decision-making is an effective method for ranking risks in situations of low samples compared with other methods of MCDM.

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Conclusion: The proposed method is preferred to fuzzy methods and statistics in uncertain and low sample size, due to simple calculations and no need to define the membership function.

Full-Text [PDF 454 kb]   (4319 Downloads)    
Type of Study: Research |
Received: 2014/09/29 | Accepted: 2014/09/29 | Published: 2014/09/29

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