Safety and Health at Work

  • 제13권3호
  • /
  • Pages.326-335
  • /
  • 2022
  • /
  • 2093-7911(pISSN)
  • /
  • 2093-7997(eISSN)
산업안전보건연구원 (Occupational Safety and Health Research Institute, Korea Occupational Safety and Health Agency)
권호 표지
DOI QR코드

DOI QR Code

Human Error Probability Determination in Blasting Process of Ore Mine Using a Hybrid of HEART and Best-Worst Methods

  • Aliabadi, Mostafa Mirzaei (Center of Excellence for Occupational Health, Occupational Health and Safety Research Center, Hamadan University of Medical Sciences) ;
  • Mohammadfam, Iraj (Center of Excellence for Occupational Health, Occupational Health and Safety Research Center, Hamadan University of Medical Sciences) ;
  • Soltanian, Ali Reza (Modeling of Non Communicable Diseases Research Center, Department of Biostatistics, School of Public Health, Hamadan University of Medical Sciences) ;
  • Najafi, Kamran (Occupational Health and Safety Research Center, Department of Occupational Health, School of Public Health, Hamadan University of Medical Sciences)
  • 투고 : 2021.11.23
  • 심사 : 2022.03.25
  • 발행 : 2022.09.30
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

Background: One of the important actions for enhancing human reliability in any industry is assessing human error probability (HEP). The HEART technique is a robust tool for calculating HEP in various industries. The traditional HEART has some weaknesses due to expert judgment. For these reasons, a hybrid model is presented in this study to integrate HEART with Best-Worst Method. Materials Method: In this study, the blasting process in an iron ore mine was investigated as a case study. The proposed HEART-BWM was used to increase the sensitivity of APOA calculation. Then the HEP was calculated using conventional HEART formula. A consistency ratio was calculated using BWM. Finally, for verification of the HEART-BWM, HEP calculation was done by traditional HEART and HEART-BWM. Results: In the view of determined HEPs, the results showed that the mean of HEP in the blasting of the iron ore process was 2.57E-01. Checking the full blast of all the holes after the blasting sub-task was the most dangerous task due to the highest HEP value, and it was found 9.646E-01. On the other side, obtaining a permit to receive and transport materials was the most reliable task, and the HEP was 8.54E-04. Conclusion: The results showed a good consistency for the proposed technique. Comparing the two techniques confirmed that the BWM makes the traditional HEART faster and more reliable by performing the basic comparisons.

키워드

과제정보

The author gratefully acknowledges the financial aid from Hamadan University of Medical Sciences (Grant No: 1400011060).

참고문헌

  1. Kecojevic V, Komljenovic D, Groves W, Radomsky M. An analysis of equipment-related fatal accidents in US mining operations: 1995-2005. Saf Sci 2007;45(8):864-74. https://doi.org/10.1016/j.ssci.2006.08.024
  2. Dash AK, Bhattcharjee R, Paul P, Tikader M. Study and analysis of accidents due to wheeled trackless transportation machinery in indian coal minese-identification of gap in current investigation system. Proced Earth Planet Sci 2015;11:539-47. https://doi.org/10.1016/j.proeps.2015.06.056
  3. Permana H. Risk assessment as a strategy to prevent of mine accidents in Indonesian mining. Revista Minelor/mining Revue. 2012;18(4).
  4. Bonsu J, Van Dyk W, Franzidis J, Petersen F, Isafiade A. A systemic study of mining accident causality: an analysis of 91 mining accidents from a platinum mine in South Africa. J Souther Afr Inst Min Metallur 2017;117(1):59-66. https://doi.org/10.17159/2411-9717/2017/v117n1a9
  5. Rushworth A, Talbot C, Von Glehn F, Lomas R. Investigate the causes of transport and tramming accidents on coal mines; 1999.
  6. Zhang Y, Jing L, Bai Q, Liu T, Feng Y. A systems approach to extraordinarily major coal mine accidents in China from 1997 to 2011: an application of the HFACS approach. Int J Occupat Saf Ergon 2019;25(2):181-93. https://doi.org/10.1080/10803548.2017.1415404
  7. Patterson JM, Shappell SA. Operator error and system deficiencies: analysis of 508 mining incidents and accidents from Queensland, Australia using HFACS. Accid Analy Preven 2010;42(4):1379-85. https://doi.org/10.1016/j.aap.2010.02.018
  8. Yin W, Fu G, Yang C, Jiang Z, Zhu K, Gao Y. Fatal gas explosion accidents on Chinese coal mines and the characteristics of unsafe behaviors: 2000-2014. Saf Sci 2017;92:173-9. https://doi.org/10.1016/j.ssci.2016.09.018
  9. Aghaei H, Mirzaei Aliabadi M, Mollabahrami F, Najafi K. Human reliability analysis in de-energization of power line using HEART in the context of Znumbers. Plos One 2021;16(7):e0253827. https://doi.org/10.1371/journal.pone.0253827
  10. Wang Q, Zhang L, Hu J. An integrated method of human error likelihood assessment for shale-gas fracturing operations based on SPA and UAHP. Proc Saf Environ Protec 2019;123:105-15. https://doi.org/10.1016/j.psep.2019.01.003
  11. Swain AD. Handbook of human reliability analysis with emphasis on nuclear power plant applications. NUREG/CR-1278, SAND 80-0200. 1983.
  12. Gertman D, Blackman H, Marble J, Byers J, Smith C. The SPAR-H human reliability analysis method. US Nuc Reg Comm 2005;230(4):35.
  13. Hollnagel E. Cognitive reliability and error analysis method (CREAM). Elsevier; 1998.
  14. Chang Y, Mosleh A. Cognitive modeling and dynamic probabilistic simulation of operating crew response to complex system accidents: Part 1: overview of the IDAC Model. Reliab Eng Syst Safety 2007;92(8):997-1013. https://doi.org/10.1016/j.ress.2006.05.014
  15. Swain AD. Accident sequence evaluation program: human reliability analysis procedure. Sandia National Labs., Albuquerque, NM (USA); Nuclear Regulatory Commission; 1987.
  16. Ekanem NJ, Mosleh A, Shen S-H. Phoenixe-a model-based human reliability analysis methodology: qualitative analysis procedure. Reliab Engin Sys Saf 2016;145:301-15. https://doi.org/10.1016/j.ress.2015.07.009
  17. Williams J, editor. A data-based method for assessing and reducing human error to improve operational performance. Conference Record for 1988 IEEE Fourth Conference on Human Factors and Power Plants. editor. IEEE; 1988.
  18. Wang W, Liu X, Qin Y. A modified HEART method with FANP for human error assessment in high-speed railway dispatching tasks. Int J Indus Ergon 2018;67:242-58. https://doi.org/10.1016/j.ergon.2018.06.002
  19. Zhou J-L, Lei Y. A slim integrated with empirical study and network analysis for human error assessment in the railway driving process, vol. 204. Reliability Engineering & System Safety; 2020. 107148 p. https://doi.org/10.1016/j.ress.2020.107148
  20. Akyuz E, Celik M. A hybrid human error probability determination approach: the case of cargo loading operation in oil/chemical tanker ship. J Loss Preven Proc Indus 2016;43:424-31. https://doi.org/10.1016/j.jlp.2016.06.020
  21. Islam R, Anantharaman M, Khan F, Abbassi R, Garaniya V. A hybrid human reliability assessment technique for the maintenance operations of marine and offshore systems. Proc Saf Prog 2020;39:e12118. https://doi.org/10.1002/prs.12118
  22. Can GF, Delice EK. An advanced human error assessment approach: HEART and AV-DEMATEL. Hum Fact Ergonom Manuf Serv Indus 2020;30(1):29-49. https://doi.org/10.1002/hfm.20819
  23. Evans M, He Y, Maglaras L, Janicke H. HEART-IS: a novel technique for evaluating human error-related information security incidents. Comp Secur 2019;80:74-89. https://doi.org/10.1016/j.cose.2018.09.002
  24. Mirzaei Aliabadi M, Mohammadfam I, Salimi K. Identification and evaluation of maintenance error in catalyst replacement using the HEART technique under a fuzzy environment. Int J Occup Saf Ergon 2021:1-13.
  25. Casamirra M, Castiglia F, Giardina M, Tomarchio E. Fuzzy modelling of HEART methodology: application in safety analyses of accidental exposure in irradiation plants. Rad Eff Def Solids 2009;164(5-6):291-6. https://doi.org/10.1080/10420150902805153
  26. Castiglia F, Giardina M. Analysis of operator human errors in hydrogen refuelling stations: comparison between human rate assessment techniques. Int J Hydrog Energ 2013;38(2):1166-76. https://doi.org/10.1016/j.ijhydene.2012.10.092
  27. Chen M-S, Lin M-C, Wang C-C, Chang CA. Using HCA and TOPSIS approaches in personal digital assistant menue-icon interface design. Int J Indust Ergonom 2009;39(5):689e702.
  28. Guo Y, Sun Y. Flight safety assessment based on an integrated human reliability quantification approach. PloS One 2020;15(4):e0231391. https://doi.org/10.1371/journal.pone.0231391
  29. Aliabadi MM. Human error analysis in furnace start-up operation using HEART under intuitionistic fuzzy environment. J Loss Preven Proc Indus 2021;69:104372. https://doi.org/10.1016/j.jlp.2020.104372
  30. Ung S-T. Evaluation of human error contribution to oil tanker collision using fault tree analysis and modified fuzzy Bayesian Network based CREAM. Ocean Engineering 2019;179:159-72. https://doi.org/10.1016/j.oceaneng.2019.03.031
  31. Kumar AM, Rajakarunakaran S, Prabhu VA. Application of Fuzzy HEART and expert elicitation for quantifying human error probabilities in LPG refuelling station. J Loss Preven Process Indus 2017;48:186-98. https://doi.org/10.1016/j.jlp.2017.04.021
  32. Wang W, Liu X, Liu S. A hybrid evaluation method for human error probability by using extended DEMATEL with Z-numbers: a case of cargo loading operation. Int J Indus Ergon 2021;84:103158. https://doi.org/10.1016/j.ergon.2021.103158
  33. Rezaei J. Best-worst multi-criteria decision-making method. Omega 2015;53:49-57. https://doi.org/10.1016/j.omega.2014.11.009
  34. Rezaei J. Best-worst multi-criteria decision-making method: some properties and a linear model. Omega 2016;64:126-30. https://doi.org/10.1016/j.omega.2015.12.001
  35. Leape LL, Abookire S. WHO draft guidelines for adverse event reporting and learning systems: from information to action. World Health Organization;2005.