Volume 8, Issue 2 (Summer 2021)
johe 2021, 8(2): 8-15 |
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Mirzaei Aliabadi M, Askaripoor T, Aghaei H. Investigation of the Relationship among Human Factors in Mining Accidents Using a Systematic Approach. johe 2021; 8 (2) :8-15
URL: http://johe.umsha.ac.ir/article-1-604-en.html
URL: http://johe.umsha.ac.ir/article-1-604-en.html
1- Center of Excellence for Occupational Health (CEOH) and Occupational Health and Safety Research Center, Hamadan University of Medical Sciences, Iran
2- Research Center for Health Sciences and Technologies, Semnan University of Medical Sciences, Semnan, Iran
3- Department of Occupational Health Engineering, Faculty of Health, Arak University of Medical Sciences, Arak, Iran , Hamedaghaeih@gmail.com
2- Research Center for Health Sciences and Technologies, Semnan University of Medical Sciences, Semnan, Iran
3- Department of Occupational Health Engineering, Faculty of Health, Arak University of Medical Sciences, Arak, Iran , Hamedaghaeih@gmail.com
Abstract: (2106 Views)
Background and Objective: Systematic analysis of accidents in sociotechnical systems, such as mining industry, is very important to reduce accidents. The present study aimed to analyze the relationship among human factors in mining accidents using a systematic approach.
Materials and Methods: The accidents occurred during seven years in a large iron ore mine complex in the south of Iran were collected, and the most important events were selected subsequently. Afterward, all contributing factors in each accident were identified using an accident analysis team by Human Factors Analysis and Classification System (HFACS) framework. A total of 154 accidents were collected, and the data were analyzed in SPSS Software (version 16) using logistic regression.
Results: Skill-based errors were the most frequent among the unsafe acts. Furthermore, the deficiencies in physical environment, as well as inappropriate operations and organizational procedures were the most frequently identified deficiency in the selected accidents. Throughout the overall system, the existence of some deficiencies in upper levels predicted those in lower levels, which included organizational climate, inadequate supervision, organizational procedures and inappropriate operations, inadequate supervision and physical environment, as well as inappropriate operations and physical environment.
Conclusion: Skill-based errors, supervision problems, and organizational procedures are the most common deficiencies in mining industry accidents. Analysis of the relationship among the causal factors at different levels of HFACS is necessary to adopt appropriate strategies to reduce the accidents.
Materials and Methods: The accidents occurred during seven years in a large iron ore mine complex in the south of Iran were collected, and the most important events were selected subsequently. Afterward, all contributing factors in each accident were identified using an accident analysis team by Human Factors Analysis and Classification System (HFACS) framework. A total of 154 accidents were collected, and the data were analyzed in SPSS Software (version 16) using logistic regression.
Results: Skill-based errors were the most frequent among the unsafe acts. Furthermore, the deficiencies in physical environment, as well as inappropriate operations and organizational procedures were the most frequently identified deficiency in the selected accidents. Throughout the overall system, the existence of some deficiencies in upper levels predicted those in lower levels, which included organizational climate, inadequate supervision, organizational procedures and inappropriate operations, inadequate supervision and physical environment, as well as inappropriate operations and physical environment.
Conclusion: Skill-based errors, supervision problems, and organizational procedures are the most common deficiencies in mining industry accidents. Analysis of the relationship among the causal factors at different levels of HFACS is necessary to adopt appropriate strategies to reduce the accidents.
Type of Study: Research Article |
Subject:
Safety
Extended Abstract [HTML 19 KB] (36 Download)
References
1. Feyer AM, Williamson AM, Stout N, Driscoll T, Usher H, Langley JD. Comparison of work-related fata injuries in the United States, Australia, and New Zealand: Method and overall findings. Inj Prev. 2001;7(1):22–8. PMID: 11289530 DOI: 10.1136/ip.7.1.22 [DOI] [PubMed]
2. Li WC, Harris D. Pilot error and its relationship with higher organizational levels: HFACS analysis of 523 accidents. Aviat Sp Environ Med. 2006;77(10):1056-61. PMID: 17042251 [PubMed]
3. Reason J. Human error. Cambridge: Cambridge University Press; 1990. P. 1056-7.
4. Wiegmann DA, Shappell SA. A human error approach to aviation accident analysis: The human factors analysis and classification system. London: Routledge; 2012. P. 1-165.
5. Chen ST, Wall A, Davies P, Yang Z, Wang J, Chou YH. A human and organisational factors (HOFs) analysis method for marine casualties using HFACS-Maritime Accidents (HFACS-MA). Saf Sci. 2013;60:105-14. DOI: 10.1016/j. ssci.2013.06.009 [DOI]
6. Wang YF, Xie M, Chin KS, Fu XJ. Accident analysis model based on bayesian network and evidential reasoning approach. J Loss Prev Process Ind. 2013;26(1):10–21. DOI: 10.1016/j.jlp.2012.08.001 [DOI]
7. Mitchell RJ, Williamson A, Molesworth B. Application of a human factors classification framework for patient safety to identify precursor and contributing factors to adverse clinical incidents in hospital. Appl Ergon. 2016;52:185-95. PMID: 26360210 DOI: 10.1016/j.apergo.2015.07.018 [DOI] [PubMed]
8. Diller T, Helmrich G, Dunning S, Cox S, Buchanan A, Shappell S. The human factors analysis classification system (HFACS) applied to health care. Am J Med Qual. 2014;29(3):181-90. PMID: 23814026 DOI: 10.1177/1062860613491623 [DOI] [PubMed]
9. Zhan Q, Zheng W, Zhao B. A hybrid human and organizational analysis method for railway accidents based on HFACS-Railway Accidents (HFACS-RAs). Saf Sci. 2017;91:232-50. DOI: 10.1016/j.ssci.2016.08.017 [DOI]
10. Reinach S, Viale A. Application of a human error framework to conduct train accident/incident investigations. Accid Anal Prev. 2006;38(2):396-406. PMID: 16310153 DOI: 10.1016/j.aap.2005.10.013 [DOI] [PubMed]
11. Paul PS, Maiti J. The synergic role of sociotechnical and personal characteristics on work injuries in mines. Ergonomics. 2008;51(5):737-67. PMID: 18432449 DOI: 10.1080/00140130701747483 [DOI] [PubMed]
12. Alper SJ, Karsh BT. A systematic review of safety violations in industry. Accid Anal Prev. 2009;41(4):739-54. PMID: 19540963 DOI: 10.1016/j.aap.2009.03.013 [DOI] [PubMed]
13. Wilson PF, Dell LD, Anderson GF. Root cause analysis : a tool for total quality management. Mexico: ASQC Quality Press; 1993. P. 216.
14. Mirzaei Aliabadi M, Aghaei H, Kalatpour O, Soltanian AR, Nikravesh A. Analysis of human and organizational factors that influence mining accidents based on Bayesian network. Int J Occup Saf Ergon. 2018;26(4):670-77. PMID: 29560801 DOI: 10.1080/10803548.2018.1455411 [DOI] [PubMed]
15. Mirzaei Aliabadi M, Aghaei H, Kalatpour O, Soltanian AR, SeyedTabib M. Effects of human and organizational deficiencies on workers’ safety behavior at a mining site in Iran. Epidemiol Health. 2018;40:e2018019. PMID: 29807409 DOI: 10.4178/epih.e2018019 [DOI] [PubMed]
16. Patterson JM, Shappell SA. Operator error and system deficiencies: Analysis of 508 mining incidents and accidents from Queensland, Australia using HFACS. Accid Anal Prev. 2010;42(4):1379-85. PMID: 20441855 DOI: 10.1016/j.aap.2010.02.018 [DOI] [PubMed]
17. Lenné MG, Salmon PM, Liu CC, Trotter M. A systems approach to accident causation in mining: An application of the HFACS method. Accid Anal Prev. 2012;48:111-7. PMID: 22664674 DOI: 10.1016/j.aap.2011.05.026 [DOI] [PubMed]
18. Mirzaei Aliabadi M, Aghaei H, Kalatpour O, Soltanian AR, Nikravesh A. Analysis of human and organizational factors that influence mining accidents based on Bayesian network. Int J Occup Saf Ergon. 2020;26(4):670-7. DOI: 10.1080/10803548.2018.1455411 [DOI]
19. Patterson JM. Human error in mining : a multivariable analysis of mining accidents / incidents in queensland, Australia and the united states of America using the human factors analysis and classification system framework. Clemson, South Carolina: Clemson University; 2009.
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