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Volume 8, Issue 1 (Iranian Journal of Ergonomics 2020)                   Iran J Ergon 2020, 8(1): 12-20 | Back to browse issues page


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Amiri Ebrahimabadi A, Soltanzadeh A, Ghiyasi S. Analysis of Occupational Accidents Based on the Human Factors Analysis and Classification System (HFACS): A Case Study in a Copper Mine. Iran J Ergon 2020; 8 (1) :12-20
URL: http://journal.iehfs.ir/article-1-691-en.html
1- MSc, Department of Health, Safety, and Environment, Faculty of Engineering, Central Tehran Branch, Islamic Azad University, Tehran, Iran.
2- Assistant Professor, Department of Occupational Safety & Hygiene Engineering, Research Center for Environmental Pollutants, Faculty of Health, Qom University of Medical Sciences, Qom, Iran , soltanzadeh.ahmad@gmail.com
3- Assistant Professor, Department of Environmental Engineering, Central Tehran Branch, Islamic Azad University, Tehran, Iran
Abstract:   (7043 Views)

Background and Aim: Occupational accidents are recognized as one of the major concerns in the mining industry. The purpose of this study was to analyze the incidence of occupational accidents in a mine for 10 years using Human Factor Analysis and Classification System (HFACS).
Method: This cross-sectional study was carried out on 664 mining accidents during 2009-2018. The tools used in this study included accident reporting checklists, human factors analysis and classification system (HFACS), and a team approach to analyze these accidents. Data analysis was performed using IBM SPSS AMOS v. 23.0.
Results: The accident frequency rate (AFR) was 15.10±3.34. The results of 10-years accident analysis in this mine based on HFACS model showed that the highest contribution of each parameter to the four layers including unsafe acts, preconditions for unsafe acts, unsafe supervision and organizational influences were respectively devoted to perceptual error (64.4%), Physical environment (29.5%), inadequate supervision (59.6%), and organizational process (65.6%). The results of structural equation modeling showed that the AFR is directly and indirectly affected by the layers of the HFACS model (P<0.05). The most significant impact on the AFR was related to the unsafe acts layer.
Conclusion: The findings of this study indicated that all four causal layers of human factors were effective in mine accidents, in addition the HFACS model is highly effective for unsafe acts-based accidents analysis, so it can be used for future planning to reduce accidents in the mining sector.

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The findings of this study indicated that all four causal layers of human factors were effective in mine accidents, in addition the HFACS model is highly effective for unsafe acts-based accidents analysis, so it can be used for future planning to reduce accidents in the mining sector.


Type of Study: Research | Subject: Other Cases
Received: 2020/02/8 | Accepted: 2020/06/6 | ePublished: 2020/06/6

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