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Articles

Fuzzy risk assessment for mechanized underground coal mines in Turkey

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References

  • Samantra C, Datta S, Mahapatra SS. A risk-based decision support framework for selection of appropriate safety measure system for underground coal mines. Int J Inj Contr Saf Promot. 2017;24(1):54–68. doi: 10.1080/17457300.2015.1061561
  • Mahdevari S, Shahriar K, Esfahanipour A. Human health and safety risks management in underground coal mines using fuzzy topsis. Sci Total Environ. 2014;488–489:85–99. doi: 10.1016/j.scitotenv.2014.04.076
  • Isabel L, Mario SM. Applications of fuzzy logic in risk assessment – the RA_X case. In: Mohammad FA, editor. Fuzzy inference system theory and applications. Rijeka: InTech; 2012. p. 21–40.
  • Iannacchione AT, Brady TM, Varley F. The application of major hazard risk assessment (MHRA) to eliminate multiple fatality occurrences in the US minerals industry. Spokane (WA): Department of Health and Human Services; 2008. (Information circular 9508; DHHS (NIOSH) Publication No. 2009-104).
  • Joy J. Occupational safety risk management in Australian mining. Occup Med-C. 2004;54(5):311–315. doi: 10.1093/occmed/kqh074
  • Gürcanli GE, Müngen U. An occupational safety risk analysis method at construction sites using fuzzy sets. Int J Ind Ergon. 2009;39(2):371–387. doi: 10.1016/j.ergon.2008.10.006
  • Gul M, Guneri AF. A fuzzy multi criteria risk assessment based on decision matrix technique: a case study for aluminum industry. J Loss Prev Process Ind. 2016;40:89–100. doi: 10.1016/j.jlp.2015.11.023
  • Sari M, Duzgun HSB, Karpuz C, et al. Accident analysis of two Turkish underground coal mines. Saf Sci. 2004;42(8):675–690. doi: 10.1016/j.ssci.2003.11.002
  • Pokoradi L. Fuzzy logic-based risk assessment. Acad Appl Res Mil Sci. 2002;1(1):63–73.
  • NSW Government, Industry & Investment Risk assessment workbook for mines: metalliferous, extractive and opal mines, and quarries. Sydney (NSW): Mine Safety Operations; 2009. (IGA-019).
  • Türkşen IB, Fazel Zarandi MH. Production planning and scheduling – fuzzy and crisp approaches. In: Zimmermann HJ, editor. Practical applications of fuzzy technologies. Norwell (MA): Kluwer Academic; 1999. p. 479–529.
  • Skorupski J. The simulation-fuzzy method of assessing the risk of air traffic accidents using the fuzzy risk matrix. Saf Sci. 2016;88:76–87. doi: 10.1016/j.ssci.2016.04.025
  • Carr V, Tah JHM. A fuzzy approach to construction project risk assessment and analysis: construction project risk management system. Adv Eng Softw. 2001;32(10):847–857. doi: 10.1016/S0965-9978(01)00036-9
  • Zeng J, An M, Smith, NJ. Application of a fuzzy based decision making methodology to construction project risk assessment. Int J Proj Manag. 2007;25(6):589–600. doi: 10.1016/j.ijproman.2007.02.006
  • Markowski AS, Mannan MS. Fuzzy logic for piping risk assessment (pfLOPA). J Loss Prev Process Ind. 2009;22(6):921–927. doi: 10.1016/j.jlp.2009.06.011
  • Tadic D, Djapan M, Misita M, et al. A fuzzy model for assessing risk of occupational safety in the processing industry. Int J Occup Saf Ergon. 2012;18(2):115–126. doi: 10.1080/10803548.2012.11076922
  • Markowski AS, Mannan MS. Fuzzy risk matrix. J Hazard Mater. 2008;159(1):152–157. doi: 10.1016/j.jhazmat.2008.03.055
  • An M, Qin Y, Jia LM, et al. Aggregation of group fuzzy risk information in the railway risk decision making process. Saf Sci. 2016;82:18–28. doi: 10.1016/j.ssci.2015.08.011
  • Ghasemi E, Ataei M, Shahriar K. Improving the method of roof fall susceptibility assessment based on fuzzy approach. Arch Min Sci. 2017;62(1):13–32.
  • Karimpour K, Zarghami R, Moosavian MA, et al. New fuzzy model for risk assessment based on different types of consequences. Oil Gas Sci Technol. 2016;71(1):17. doi:doi: 10.2516/ogst/2014044
  • Nieto-Morote A, Ruz-Vila F. A fuzzy approach to construction project risk assessment. Int J Proj Manag. 2011;29(2):220–231. doi: 10.1016/j.ijproman.2010.02.002
  • Ossama YA, Walied B. Application of fuzzy logic for risk assessment using risk matrix. Int J Emerg Technol Adv Eng. 2013;3(1):49–54.
  • Golmohammadi R, Eshaghi M, Khoram MR. Fuzzy logic method for assessment of noise exposure risk in an industrial workplace. Int J Occup Hyg. 2011;3(2):49–55.
  • Chang K-H, Cheng C-H. A risk assessment methodology using intuitionistic fuzzy set in FMEA. Int J Syst Sci. 2010;41(12):1457–1471. doi: 10.1080/00207720903353633
  • Miri Lavasani SM, Yang Z, Finlay J, et al. Fuzzy risk assessment of oil and gas offshore wells. Process Saf Environ Prot. 2011;89(5):277–294. doi: 10.1016/j.psep.2011.06.006
  • Kang J, Liang W, Zhang L, et al. A new risk evaluation method for oil storage tank zones based on the theory of two types of hazards. J Loss Prev Process Ind. 2014;29:267–276. doi: 10.1016/j.jlp.2014.03.007
  • Ghasemi E, Ataei M. Application of fuzzy logic for predicting roof fall rate in coal mines. Neural Comput Appl. 2013;22(Suppl 1):311–321. doi: 10.1007/s00521-012-0819-3
  • Ghasemi E, Ataei M, Shahriar K. An intelligent approach to predict pillar sizing in designing room and pillar coal mines. Int J Rock Mech Min. 2014;65:86–95.
  • Ghasemi E, Ataei M, Shahriar K. Prediction of global stability in room and pillar coal mines. Nat Hazard. 2014;72(2):405–422. doi: 10.1007/s11069-013-1014-2
  • Eratak ÖD. Analysis and modelling for risk management for underground coal mines’ safety [dissertation]. Ankara: Middle East Technical University; 2014.
  • Wang Q, Wang H, Qi Z. An application of nonlinear fuzzy analytic hierarchy process in safety evaluation of coal mine. Saf Sci. 2016;86:78–87. doi: 10.1016/j.ssci.2016.02.012
  • Samantra C, Datta S, Mahapatra SS. Analysis of occupational health hazards and associated risks in fuzzy environment: a case research in an Indian underground coal mine. Int J Inj Contr Saf Promot. 2017;24(3):311–327. doi: 10.1080/17457300.2016.1178298
  • Rezakhani P. A review of fuzzy risk assessment models for construction projects. Slovak J Civ Eng. 2012;20(3):35–40.
  • Rezakhani P. Current state of existing project risk modeling and analysis methods with focus on fuzzy risk assessment – literature review. Frattura ed Integritá Strutturale. 2012;20:17–21.
  • Yazdani-Chamzini, A. Proposing a new methodology based on fuzzy logic for tunnelling risk assessment. J Civ Eng Manag. 2014;20(1):82–94. doi: 10.3846/13923730.2013.843583
  • Dikmen I, Birgonul MT, Han S. Using fuzzy risk assessment to rate cost overrun risk in international construction projects. Int J Proj Manag. 2007;25(5):494–505. doi: 10.1016/j.ijproman.2006.12.002
  • Wang L, Wang Y, Cao Q, et al. A framework for human error risk analysis of coal mine emergency evacuation in China. J Loss Prev Process Ind. 2014;30:113–123. doi: 10.1016/j.jlp.2014.05.007
  • Vatanpour S, Hrudey SE, Dinu I. Can public health risk assessment using risk matrices be misleading? Int J Environ Res Public Health. 2015;12(8):9575–9588. doi: 10.3390/ijerph120809575
  • Kirchsteiger C. On the use of probabilistic and deterministic methods in risk analysis. J Loss Prev Process Ind. 1999;12(5):399–419. doi: 10.1016/S0950-4230(99)00012-1
  • Pérez-Fernández R, Alonso P, Díaz I, et al. Multi-factorial risk assessment: an approach based on fuzzy preference relations. Fuzzy Set Syst. 2015;278:67–80. doi: 10.1016/j.fss.2014.10.012
  • Grassi A, Gamberini R, Mora C, et al. A fuzzy multi-attribute model for risk evaluation in workplaces. Saf Sci. 2009;47(5):707–716. doi: 10.1016/j.ssci.2008.10.002
  • Zadeh LA. Fuzzy sets. Inf Control. 1965;8:338–353. doi: 10.1016/S0019-9958(65)90241-X
  • Ross T. Fuzzy logic with engineering applications. New York (NY): McGraw-Hill; 1995.
  • Jang RJS, Sun CT, Mizutani E. Neuro-fuzzy and soft computing. Upper Saddle River (NJ): Prentice-Hall; 1997.
  • Meng Tay K, Peng Lim CP. Fuzzy FMEA with a guided rules reduction system for prioritization of failures. Int J Qual Reliab Manag. 2006;23(8):1047–1066. doi: 10.1108/02656710610688202
  • Cukurluoz AK. Mekanize yeralti kömür ocaklarinda bulanik mantik yaklaşimiyla risk değerlendirmesi. [Risk assessment for mechanized underground coal mines by fuzzy logic approach] [master’s thesis]. Eskisehir: Eskisehir Osmangazi University Graduate School of Natural and Applied Sciences; Forthcoming. Turkish.
  • Safety and health in underground coal mines: ILO code of practice. Geneva: International Labour Office; 2009.
  • Turkish Standards Institution (TSE). [Respiratory protective devices – self-contained closed-circuit breathing apparatus for escape – requirements, testing, marking]. Ankara: TSE; 2006. Standard No. TS EN 13794:2006. Turkish.
  • What happened in Soma? Mining Turkey [Internet]. 2014 Oct [cited 2017 Aug 30]; Documentary: [7 pages]. Available from: http://www.miningturkeymag.com/pdfler/mak-1413460635.pdf

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