Skip to main content

Learning from Fire Accident at Bouali Sina Petrochemical Complex Plant

Journal of Failure Analysis and Prevention volume 19, pages 1517–1536 (2019)Cite this article

Abstract

The dependency of the society on the hydrocarbon as an energy source has increased tremendously, leading to the rapid development of this process industry. A fire accident that occurred on the 6th of July 2016 at a petrochemical complex plant in the southern part of Iran, Mahshahr petrochemical zone, has called for a more robust and all-inclusive efforts toward ameliorating and forestalling future occurrence. The on-site investigations concluded that the fire was triggered by the leakages through the ruptured blind flange gasket in the pipeline. Thus, certain inquiries on the development of robust process safety technologies gave useful insight into those capable enough to identify and handle various uncertainties in the short and long time basis, to forestall catastrophic accidents. Therefore, it is worthy and pertinent to ascertain whether process safety technology is developing correspondingly at the same pace with the process industry. Are the correct things done in the right way? If yes, then why do these catastrophic accidents keep happening? If no, how can these uncertainties in the process be properly and adequately handled, contained and managed? Failure to provide adequate and incontrovertible answers to these questions toward taking uncompromising safety actions is an invitation to more accidents in the near future. In this study, explanation on how to identify and cope with various uncertainties in process safety science is provided through learning from a real case study of a fire accident that occurred in the aforementioned petrochemical plant.

This is a preview of subscription content, access via your institution.

Access options

Buy single article

Instant access to the full article PDF.

USD 39.95

Price includes VAT (USA)
Tax calculation will be finalised during checkout.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18
Fig. 19
Fig. 20
Fig. 21
Fig. 22

Modified after Henderson et al. [53]

Fig. 23

Adopted and modified after [71]

Fig. 24

References

  1. Tasnim, Big fire at Iran petchem plant goes out after 57 hours, Tasnim News Agency (2016). https://www.tasnimnews.com/en/news/2016/07/09/1124784/big-fire-at-iran-petchem-plant-goes-out-after-57-hours. Accessed 9 July 2016

  2. A. Al-shanini, A. Ahmad, F. Khan, Accident modelling and analysis in process industries. J. Loss Prev. Process Ind. 32, 319–334 (2014). https://doi.org/10.1016/j.jlp.2014.09.016

    Article  Google Scholar 

  3. Bouali Sina Fire Accident Report (HSE Department, Mahshahr, 2016). (in Persian). https://up.20script.ir/file/10c4-Bouali-Sina-Fire-Accident-Report-HSE-Department-Mahshahr-2016-in-Persian-.pdf

  4. S.J. Hashemi, F. Khan, S. Ahmed, Multivariate probabilistic safety analysis of process facilities using the Copula Bayesian Network model. Comput. Chem. Eng. 93, 128–142 (2016). https://doi.org/10.1016/j.compchemeng.2016.06.011

    CAS  Article  Google Scholar 

  5. A.S. Markowski, M. Sam Mannan, ExSys-LOPA for the chemical process industry. J. Loss Prev. Process Ind. 23, 688–696 (2010). https://doi.org/10.1016/j.jlp.2010.05.011

    CAS  Article  Google Scholar 

  6. M. Yazdi, The application of bow-tie method in hydrogen sulfide risk management using layer of protection analysis (LOPA). J. Fail. Anal. Prev. 17, 291–303 (2017). https://doi.org/10.1007/s11668-017-0247-x

    Article  Google Scholar 

  7. H. Zerrouki, H. Smadi, Bayesian belief network used in the chemical and process industry: a review and application. J. Fail. Anal. Prev. 17, 159–165 (2017). https://doi.org/10.1007/s11668-016-0231-x

    Article  Google Scholar 

  8. M. Giardina, M. Morale, Safety study of an LNG regasification plant using an FMECA and HAZOP integrated methodology. J. Loss Prev. Process Ind. 35, 35–45 (2015). https://doi.org/10.1016/J.JLP.2015.03.013

    CAS  Article  Google Scholar 

  9. A.S. Markowski, D. Siuta, Fuzzy logic approach to calculation of thermal hazard distances in process industries. Process Saf. Environ. Prot. 92, 338–345 (2014). https://doi.org/10.1016/j.psep.2014.02.005

    CAS  Article  Google Scholar 

  10. A.S. Markowski, M.S. Mannan, A. Kotynia, D. Siuta, Uncertainty aspects in process safety analysis. J. Loss Prev. Process Ind. 23, 446–454 (2010). https://doi.org/10.1016/j.jlp.2010.02.005

    Article  Google Scholar 

  11. M. Yazdi, An extension of fuzzy improved risk graph and fuzzy analytical hierarchy process for determination of chemical complex safety integrity levels. Int. J. Occup. Saf. Ergon. 25, 551–561 (2017). https://doi.org/10.1080/10803548.2017.1419654

    Article  Google Scholar 

  12. M. Yazdi, F. Nikfar, M. Nasrabadi, Failure probability analysis by employing fuzzy fault tree analysis. Int. J. Syst. Assur. Eng. Manag. 8, 1177–1193 (2017). https://doi.org/10.1007/s13198-017-0583-y

    Article  Google Scholar 

  13. T. Kletz, The history of process safety. J. Loss Prev. Process Ind. 25, 763–765 (2012). https://doi.org/10.1016/j.jlp.2012.03.011

    Article  Google Scholar 

  14. H. Zerrouki, A. Tamrabet, Safety and risk analysis of an operational heater using bayesian network. J. Fail. Anal. Prev. 15, 657–661 (2015). https://doi.org/10.1007/s11668-015-9986-8

    Article  Google Scholar 

  15. E. Mkpat, G. Reniers, V. Cozzani, Process safety education: a literature review. J. Loss Prev. Process Ind. 54, 18–27 (2018). https://doi.org/10.1016/j.jlp.2018.02.003

    Article  Google Scholar 

  16. A.S. Markowski, M.S. Mannan, A. Bigoszewska, Fuzzy logic for process safety analysis. J. Loss Prev. Process Ind. 22, 695–702 (2009). https://doi.org/10.1016/j.jlp.2008.11.011

    Article  Google Scholar 

  17. M. Yazdi, O. Korhan, S. Daneshvar, Application of fuzzy fault tree analysis based on modified fuzzy AHP and fuzzy TOPSIS for fire and explosion in process industry. Int. J. Occup. Saf. Ergon. (2018). https://doi.org/10.1080/10803548.2018.1454636

    Article  Google Scholar 

  18. M. Yazdi, Acquiring and sharing tacit knowledge in failure diagnosis analysis using intuitionistic and pythagorean assessments. J. Fail. Anal. Prev. (2019). https://doi.org/10.1007/s11668-019-00599-w

    Article  Google Scholar 

  19. M. Yazdi, S. Kabir, A fuzzy Bayesian network approach for risk analysis in process industries. Process Saf. Environ. Prot. 111, 507–519 (2017). https://doi.org/10.1016/j.psep.2017.08.015

    CAS  Article  Google Scholar 

  20. P.R. Amyotte, S. Berger, D.W. Edwards, J.P. Gupta, D.C. Hendershot, F.I. Khan, M.S. Mannan, R.J. Willey, Why major accidents are still occurring. Curr. Opin. Chem. Eng. 14, 1–8 (2016). https://doi.org/10.1016/J.COCHE.2016.07.003

    Article  Google Scholar 

  21. M.S. Mannan, O. Reyes-Valdes, P. Jain, N. Tamim, M. Ahammad, The evolution of process safety: current status and future direction. Annu. Rev. Chem. Biomol. Eng. 7, 135–162 (2016). https://doi.org/10.1146/annurev-chembioeng-080615-033640

    Article  Google Scholar 

  22. F. Khan, S. Ahmed, M. Yang, S.J. Hashemi, S. Caines, S. Rathnayaka, D. Oldford, Safety challenges in harsh environments: lessons learned. Process Saf. Prog. 34, 191–195 (2015). https://doi.org/10.1002/prs.11704

    Article  Google Scholar 

  23. M. Yazdi, A perceptual computing: based method to prioritize intervention actions in the probabilistic risk assessment techniques. Qual. Reliab. Eng. Int. (2019). https://doi.org/10.1002/qre.2566

    Article  Google Scholar 

  24. M. Yazdi, M. Darvishmotevali, Fuzzy-Based Failure Diagnostic Analysis in a Chemical Process Industry (Springer, Cham, 2019), pp. 724–731. https://doi.org/10.1007/978-3-030-04164-9_95

    Book  Google Scholar 

  25. M. Yazdi, Introducing a heuristic approach to enhance the reliability of system safety assessment. Qual. Reliab. Eng. Int. (2019). https://doi.org/10.1002/qre.2545

    Article  Google Scholar 

  26. M. Yazdi, Footprint of knowledge acquisition improvement in failure diagnosis analysis. Qual. Reliab. Eng. Int. (2018). https://doi.org/10.1002/qre.2408

    Article  Google Scholar 

  27. J.T. Reason, Human Error (Cambridge University Press, Cambridge, 1990)

    Book  Google Scholar 

  28. C. Hart, Accident Precursor Analysis and Management: Reducing Technological Risk Through Diligence (National Academies Press, Washington, 2004)

    Google Scholar 

  29. M. Yazdi, Risk assessment based on novel intuitionistic fuzzy-hybrid-modified TOPSIS approach. Saf. Sci. 110, 438–448 (2018). https://doi.org/10.1016/j.ssci.2018.03.005

    Article  Google Scholar 

  30. M. Cheraghi, A. Eslami Baladeh, N. Khakzad, A fuzzy multi-attribute HAZOP technique (FMA-HAZOP): application to gas wellhead facilities. Saf. Sci. 114, 12–22 (2019). https://doi.org/10.1016/j.ssci.2018.12.024

    Article  Google Scholar 

  31. M. Naderpour, N. Khakzad, Texas LPG fire: Domino effects triggered by natural hazards. Process Saf. Environ. Prot. 116, 354–364 (2018). https://doi.org/10.1016/J.PSEP.2018.03.008

    CAS  Article  Google Scholar 

  32. N. Khakzad, Application of dynamic Bayesian network to risk analysis of domino effects in chemical infrastructures. Reliab. Eng. Syst. Saf. 138, 263–272 (2015). https://doi.org/10.1016/j.ress.2015.02.007

    Article  Google Scholar 

  33. A. Misuri, N. Khakzad, G. Reniers, V. Cozzani, Tackling uncertainty in security assessment of critical infrastructures: Dempster-Shafer theory vs. credal sets theory. Saf. Sci. 107, 62–76 (2018). https://doi.org/10.1016/j.ssci.2018.04.007

    Article  Google Scholar 

  34. N. Khakzad, G. Reniers, Using graph theory to analyze the vulnerability of process plants in the context of cascading effects. Reliab. Eng. Syst. Saf. 143, 63–73 (2015). https://doi.org/10.1016/j.ress.2015.04.015

    Article  Google Scholar 

  35. M. Yazdi, A review paper to examine the validity of Bayesian network to build rational consensus in subjective probabilistic failure analysis. Int. J. Syst. Assur. Eng. Manag. (2019). https://doi.org/10.1007/s13198-018-00757-7

    Article  Google Scholar 

  36. N. Khakzad, Protecting chemical plants against terrorist attacks: a review. J. Soc. 05, 1–4 (2015). https://doi.org/10.4172/2167-0358.1000142

    Article  Google Scholar 

  37. S. Mannan, F.P. Lees, Lees’ Loss Prevention in the Process Industries: Hazard Identification, Assessment, and Control (Butterworth-Heinemann, Oxford, 2005)

    Google Scholar 

  38. P.G. Kovatsis, J.E. Fiadjoe, Those who cannot remember the past are condemned to repeat it. Pediatr. Anesth. 26, 333–334 (2016). https://doi.org/10.1111/pan.12861

    Article  Google Scholar 

  39. D.A. Crowl, J.F. Louvar, Chemical Process Safety: Fundamentals with Applications (Prentice Hall, Upper Saddle River, 2011)

    Google Scholar 

  40. T.A. Kletz, Still Going Wrong! Case Histories of Process Plant Disasters and How They Could have been Avoided (Gulf Professional Publishing, Houston, 2003)

    Google Scholar 

  41. M. Yazdi, E. Zarei, Uncertainty handling in the safety risk analysis: an integrated approach based on fuzzy fault tree analysis. J. Fail. Anal. Prev. (2018). https://doi.org/10.1007/s11668-018-0421-9

    Article  Google Scholar 

  42. H. Pasman, W. Rogers, How can we use the information provided by process safety performance indicators? Possibilities and limitations. J. Loss Prev. Process Ind. 30, 197–206 (2014). https://doi.org/10.1016/j.jlp.2013.06.001

    Article  Google Scholar 

  43. A. Targoutzidis, Incorporating human factors into a simplified “bow-tie” approach for workplace risk assessment. Saf. Sci. 48, 145–156 (2010). https://doi.org/10.1016/j.ssci.2009.07.005

    Article  Google Scholar 

  44. M. Yazdi, S. Kabir, M. Walker, Uncertainty handling in fault tree based risk assessment: state of the art and future perspectives. Process Saf. Environ. Prot. 131, 89–104 (2019). https://doi.org/10.1016/j.psep.2019.09.003

    CAS  Article  Google Scholar 

  45. I.L. Johansen, M. Rausand, Ambiguity in risk assessment. Saf. Sci. 80, 243–251 (2015). https://doi.org/10.1016/j.ssci.2015.07.028

    Article  Google Scholar 

  46. C. Zhang, Y. Wei, Z. Li, Y. Zhao, Hazard-based design of the bow-tie method to prevent and mitigate mine accidents. J. Fail. Anal. Prev. (2017). https://doi.org/10.1007/s11668-017-0367-3

    Article  Google Scholar 

  47. F. Aqlan, E. Mustafa Ali, Integrating lean principles and fuzzy bow-tie analysis for risk assessment in chemical industry. J. Loss Prev. Process Ind. 29, 39–48 (2014). https://doi.org/10.1016/j.jlp.2014.01.006

    CAS  Article  Google Scholar 

  48. A.S. Markowski, A. Kotynia, “Bow-tie” model in layer of protection analysis. Process Saf. Environ. Prot. 89, 205–213 (2011). https://doi.org/10.1016/j.psep.2011.04.005

    CAS  Article  Google Scholar 

  49. F. Yan, K. Xu, X. Yao, Y. Li, Fuzzy Bayesian network-bow-tie analysis of gas leakage during biomass gasification. PLoS ONE 11, e0160045 (2016). https://doi.org/10.1371/journal.pone.0160045

    CAS  Article  Google Scholar 

  50. A. Shahriar, R. Sadiq, S. Tesfamariam, Risk analysis for oil & gas pipelines: a sustainability assessment approach using fuzzy based bow-tie analysis. J. Loss Prev. Process Ind. 25, 505–523 (2012). https://doi.org/10.1016/j.jlp.2011.12.007

    Article  Google Scholar 

  51. S. Cai, J. Hu, L. Zhang, Risk analysis of refining equipment based on fuzzy theory and bow-tie model, in Chinese Control Conference CCC, 2016-Aug (2016), pp. 9704–9711. https://doi.org/10.1109/chicc.2016.7554896

  52. M. Yazdi, A. Nedjati, R. Abbassi, Fuzzy dynamic risk-based maintenance investment optimization for offshore process facilities. J. Loss Prev. Process Ind. 57, 194–207 (2019). https://doi.org/10.1016/j.jlp.2018.11.014

    Article  Google Scholar 

  53. J. Henderson, D. Embrey, R. Associates, Quantifying human reliability in risk assessments. Pet. Rev. 66, 30–32 (2012)

    Google Scholar 

  54. C.B. Holroyd, M.G.H. Coles, The neural basis of human error processing: Reinforcement learning, dopamine, and the error-related negativity. Psychol. Rev. 109, 679–709 (2002). https://doi.org/10.1037//0033-295X.109.4.679

    Article  Google Scholar 

  55. J. Reason, Human error: models and management. BMJ 320, 768–770 (2000). https://doi.org/10.1136/bmj.320.7237.768

    CAS  Article  Google Scholar 

  56. S. Kaplan, The words of risk analysis. Risk Anal. 17, 407–417 (1997). https://doi.org/10.1111/j.1539-6924.1997.tb00881.x

    Article  Google Scholar 

  57. OSHA, Process Safety Management (OSHA 3132) (OSHA, Washington, 2000)

    Google Scholar 

  58. P. Amyotte, An Introduction to Dust Explosions: Understanding the Myths and Realities of Dust Explosions for a Safer Workplace (Elsevier, Amsterdam, 2013)

    Google Scholar 

  59. Canadian Society of Chemical Engineering, Process Safety Management (2012). https://doi.org/10.1201/b11069-30

  60. B.D. Kelly, Why process safety programs sometimes fail. Process Saf. Prog. 30, 307–309 (2011). https://doi.org/10.1002/prs.10494

    Article  Google Scholar 

  61. J. Tharaldsen, K. Haukelid, Culture and behavioural perspectives on safety: towards a balanced approach. J. Risk Res. 12, 375–388 (2009). https://doi.org/10.1080/13669870902757252

    Article  Google Scholar 

  62. M.S. Mannan, R.A. Mentzer, J. Zhang, Framework for creating a best-in-class safety culture. J. Loss Prev. Process Ind. 26, 1423–1432 (2013). https://doi.org/10.1016/j.jlp.2013.09.007

    Article  Google Scholar 

  63. W.H. Glick, Conceptualizing and measuring organizational and psychological climate: pitfalls in multilevel research. Acad. Manag. Rev. 10, 601 (1985). https://doi.org/10.2307/258140

    Article  Google Scholar 

  64. A.P. Jones, L.R. James, Psychological climate: dimensions and relationships of individual and aggregated work environment perceptions. Organ. Behav. Hum. Perform. 23, 201–250 (1979). https://doi.org/10.1016/0030-5073(79)90056-4

    Article  Google Scholar 

  65. D.C. Hendershot, Guest perspective on Bhopal: why can’t we do better? Thoughts on the 30th anniversary of the Bhopal tragedy. J. Loss Prev. Process Ind. 36, 183–184 (2015). https://doi.org/10.1016/J.JLP.2015.06.011

    Article  Google Scholar 

  66. National Petochemical Compnay, Petochemcial accident report (Annually), Tehran (2017)

  67. M. Yazdi, Improving failure mode and effect analysis (FMEA) with consideration of uncertainty handling as an interactive approach. Int. J. Interact. Des. Manuf. (2018). https://doi.org/10.1007/s12008-018-0496-2

    Article  Google Scholar 

  68. T.L. Mathis, S.M. Galloway, Steps to Safety Culture Excellence (Wiley, 2013). https://www.wiley.com/en-us/Steps+to+Safety+Culture+Excellence-p-9781118098486. Accessed 7 Feb 2018

  69. M.N. Vinodkumar, M. Bhasi, Safety management practices and safety behaviour: assessing the mediating role of safety knowledge and motivation. Accid. Anal. Prev. 42, 2082–2093 (2010). https://doi.org/10.1016/j.aap.2010.06.021

    CAS  Article  Google Scholar 

  70. E. De Rademaeker, G. Suter, H.J. Pasman, B. Fabiano, A review of the past, present and future of the European loss prevention and safety promotion in the process industries. Process Saf. Environ. Prot. 92, 280–291 (2014). https://doi.org/10.1016/j.psep.2014.03.007

    CAS  Article  Google Scholar 

  71. F. Khan, S.J. Hashemi, N. Paltrinieri, P. Amyotte, V. Cozzani, G. Reniers, Dynamic risk management: a contemporary approach to process safety management. Curr. Opin. Chem. Eng. 14, 9–17 (2016). https://doi.org/10.1016/J.COCHE.2016.07.006

    Article  Google Scholar 

  72. HSE, Reducing error and influencing behaviour, HSE Books (1999). http://www.hse.gov.uk/pubns/books/hsg48.htm. Accessed 5 Feb 2018

  73. F. Khan, Methods in Chemical Process Safety, vol. 1, 1st edn. (2017)

Download references

Acknowledgment

First author would like to express his gratitude to the BSPP for supporting this study by releasing all the vital information related to the accident and for allowing us to use the Figures for publication. Our profound appreciation also goes to the experts that participated by sparing their valuable time, experience, and for the insightful comments rendered.

Author information

Authors and Affiliations

  1. Mahshahr Petrochemical Special Economic Zone, Mahshahr, Iran

    Mohammad Yazdi & Farzaneh Nikfar

  2. Food Engineering Department, Near East University, Via Mersin 10, Lefkosia, North Cyprus, TNRC, Turkey

    Kehinde Adewale Adesina

  3. Department of Industrial Engineering, Eastern Mediterranean University, 99628, Famagusta, North Cyprus, Turkey

    Orhan Korhan

Authors
  1. Mohammad Yazdi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Kehinde Adewale Adesina
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Orhan Korhan
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Farzaneh Nikfar
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Mohammad Yazdi.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Yazdi, M., Adesina, K.A., Korhan, O. et al. Learning from Fire Accident at Bouali Sina Petrochemical Complex Plant. J Fail. Anal. and Preven. 19, 1517–1536 (2019). https://doi.org/10.1007/s11668-019-00769-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11668-019-00769-w

Keywords

  • Process safety
  • Hazards
  • Resilience engineering
  • Ambiguities
  • Para-xylene
  • Fire