Skip to main content
SpringerLink
Log in

Fixed-Roof Hydrocarbon Oil Storage Tank: An Approach to Reliability Engineering Tools

  • Original Research Article
  • Published:
Journal of Failure Analysis and Prevention Aims and scope Submit manuscript

Abstract

Hydrocarbon bulk oil storage tanks are critical assets in an oil terminal and pumping station. These tanks are used for receiving, storage and pumping operations around the year. American Petroleum Institute (API) provides legislation (API-653) for their maintenance. In this study, a system of bulk storage tanks is considered along with associated instrumentation for a terminal station of one of the leading oil companies based in Karachi, Pakistan. An approach of reliability-centered maintenance (RCM) for the system and associated instrumentation is applied. A failure mode and effects analysis (FMEA) is also performed using failure data. The risk priority number (RPN) for each failure has been calculated for the existing maintenance plan and the additional recommended controls. Existing maintenance strategies are analyzed. The shortcomings are identified, and an RCM framework is proposed. The reliability of the system with and without RCM is considered. The results revealed that if the RCM approach is utilized, its reliability as of today would have been the same as it was exhibited nine years ago, that is, 99.72% which is a 0.52% increase from the case if RCM is not implemented. Furthermore, RPN decreases up to nearly 67% after implementing the proposed controls, for the storage tank foundation. This implies that the risk of damage to the tank foundation can be decreased by a staggering 67%.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

Abbreviations

API:

American Petroleum Institute

ATGS:

Auto-Tank gauging system

D :

Detection

FMEA:

Failure mode and effects analysis

FMECA:

Failure mode, effects and criticality analysis

FTA:

Fault tree analysis

HMI:

Human–machine interface

MOV:

Motor-operated valve

O :

Occurrence

RBI:

Risk-based inspection

RCM:

Reliability-centered maintenance

RPN:

Risk priority number

S :

Severity

SAP:

Systems, applications and products in data processing

SCADA:

Supervisory control and data acquisition system

References

  1. American-Petroleum-Institute, API 653: Tank Inspection, Repair, Alteration, and Reconstruction, 5th edn. (American-Petroleum-Institute, Washington, 2014), p.1–173

    Google Scholar 

  2. I. Animah, M. Shafiee, Application of risk analysis in the liquefied natural gas (LNG) sector: an overview. J. Loss Prev. Process Ind. (2020). https://doi.org/10.1016/j.jlp.2019.103980

    Article  Google Scholar 

  3. M. Baghbani, S. Iranzadeh, M.B. Khajeh, Investigating the relationship between RPN parameters in fuzzy PFMEA and OEE in a sugar factory. J. Loss Prev. Process Ind. 60, 221–232 (2019). https://doi.org/10.1016/j.jlp.2019.05.003

    Article  Google Scholar 

  4. H.S. Bakouch, M.A. Jazi, S. Nadarajah, A. Dolati, R. Roozegar, A Lifetime model with increasing failure rate. Appl. Math. Model. 38, 5392–5406 (2014). https://doi.org/10.1016/j.apm.2014.04.028

    Article  Google Scholar 

  5. J. Balaraju, M.G. Raj, C.S. Murthy, Fuzzy-FMEA risk evaluation approach for LHD machine – a case study. J. Sustain. Min. 18, 257–268 (2019). https://doi.org/10.1016/j.jsm.2019.08.002

    Article  Google Scholar 

  6. M. Bertolini, M. Bevilacqua, F.E. Ciarapica, G. Giacchettab, Development of risk-based inspection and maintenance procedures for an oil refinery. J. Loss Prev. Process Ind. 22, 244–253 (2009). https://doi.org/10.1016/j.jlp.2009.01.003

    Article  Google Scholar 

  7. E. Calixto, Reliability and maintenance. in: Calixto, E. ed. Gas and Oil Reliability Engineering. 2 ed. Gulf Professional Publishing, Boston (2016). https://doi.org/10.1016/B978-0-12-805427-7.00003-8.

  8. V.G. Cancho, F.L. Neto, G.D.C. Barriga, The Poisson-exponential lifetime distribution. Comput. Stat. Data Anal. 55, 677–686 (2011). https://doi.org/10.1016/j.csda.2010.05.033

    Article  Google Scholar 

  9. J. Carretero, J.M. Pérez, García-Carballeira, F., Calderón, A., Fernández, J. D. García, J. D., Lozano, A., Cardona, L., Cotaina, N., Prete, P., Applying RCM in large scale systems: a case study with railway networks. Reliab. Eng. Syst. Saf. 82, 257–273 (2003). https://doi.org/10.1016/S0951-8320(03)00167-4

    Article  Google Scholar 

  10. A.D. Carter, Mechanical Reliability. (MacMillan Education LTD, London, 1986)

    Book  Google Scholar 

  11. J.I. Chang, C.C. Lin, A study of storage tank accidents. J. Loss Prev. Process Ind. 19, 51–59 (2006). https://doi.org/10.1016/j.jlp.2005.05.015

    Article  Google Scholar 

  12. P. Chemweno, L. Pintelon, A.V. Horenbeek, P. Muchiri, Development of a risk assessment selection methodology for asset maintenance decision-making: an analytic network process (ANP) approach. Int. J. Prod. Econ. 170, 663–676 (2015). https://doi.org/10.1016/j.ijpe.2015.03.017

    Article  Google Scholar 

  13. Z. Chen, X. Wu, J. Qin, Risk assessment of an oxygen-enhanced combustor using a structural model based on the FMEA and fuzzy fault tree. J. Loss Prev. Process Ind. 32, 349–357 (2014). https://doi.org/10.1016/j.jlp.2014.10.004

    Article  CAS  Google Scholar 

  14. T. L. Cheng, A critical discussion on bathtub curve, in 42nd Annual Conference of the Republic of China and the 12th National Quality Management Seminar (2006) http://www.bm.nsysu.edu.tw/tutorial/iylu/conferance%20paper/B035.pdf. http://www.bm.nsysu.edu.tw/tutorial/iylu/conferance%20paper/B035.pdf.

  15. Crawley, F., Failure modes and effects analysis (FMEA) and failure modes, effects and criticality analysis (FMECA), in A Guide to Hazard Identification Methods 2ed.: Elsevier, Amsterdam (2020) https://doi.org/10.1016/B978-0-12-819543-7.00012-4.

  16. C. Crippa, L. Fiorentini, V. Rossini, R. Stefanelli, S. Tafaro, M. Marchi, Fire risk management system for safe operation of large atmospheric storage tanks. J. Loss Prev. Process Ind. 22, 574–581 (2009). https://doi.org/10.1016/j.jlp.2009.05.003

    Article  Google Scholar 

  17. F. Crotogino, Traditional bulk energy storage: coal and underground natural gas and oil storage, in T. M. Letcher ed. Storing Energy. 2 ed.: Elsevier, Amsterdam (2022) https://doi.org/10.1016/B978-0-12-824510-1.00021-0.

  18. V.S. Deshpande, J.P. Modak, Application of RCM to a medium-scale industry. Reliab. Eng. Syst. Saf. 77, 31–43 (2002). https://doi.org/10.1016/S0951-8320(02)00011-X

    Article  Google Scholar 

  19. J. Dias, E. Nunes, S. Sousa, Productivity improvement of transmission electron microscopes—a case study. Procedia Manuf. 51, 1559–1566 (2020). https://doi.org/10.1016/j.promfg.2020.10.217

    Article  Google Scholar 

  20. Ding, R., Liu, Z., Xu, J., Meng, F., Sui, Y., Men, X., 2021. A Novel Approach for Reliability Assessment of Residual Heat Removal System for HPR1000 based on Failure Mode and Effect Analysis, Fault Tree Analysis, and Fuzzy Bayesian Network Methods. Reliability Engineering and System Safety 216. https://doi.org/10.1016/j.ress.2021.107911.

  21. R. F. Drenick, The failure law of complex equipment. J. Soc. Ind. Appl. Math. 8, 680–690 (1960). http://www.jstor.org/stable/2099056.

  22. C.E. Ebeling, An Introduction to Reliability and Maintainability Engineering. (McGraw-Hill Inc, New York, 1997)

    Google Scholar 

  23. T. Elusakin, M. Shafiee, Reliability analysis of subsea blowout preventers with condition-based maintenance using stochastic petri nets. J. Loss Prev. Process Ind. (2020). https://doi.org/10.1016/j.jlp.2019.104026

    Article  Google Scholar 

  24. M.H. Enjavimadar, M. Rastegar, Optimal reliability-centred maintenance strategy based on the failure modes and effect analysis in power distribution systems. Electric Power Syst. Res. (2022). https://doi.org/10.1016/j.epsr.2021.107647

    Article  Google Scholar 

  25. S. Eriksen, I.B. Utne, M. Lützen, An RCM approach for assessing reliability challenges and maintenance needs of unmanned cargo ships. Reliab. Eng. Syst. Saf. 210, 107550 (2021). https://doi.org/10.1016/j.ress.2021.107550

    Article  Google Scholar 

  26. L. Fan, H. Su, W. Wang, E. Zio, L. Zhang, Z. Yang, S. Peng, W. Yu, L. Zuo, J. Zhang, A systematic method for the optimization of gas supply reliability in natural gas pipeline network based on bayesian networks and deep reinforcement learning. Reliab. Eng. Syst. Saf. 225, 108613 (2022). https://doi.org/10.1016/j.ress.2022.108613

    Article  Google Scholar 

  27. M.A. Filz, J.E.B. Langner, C. Herrmann, S. Thiede, Data-driven failure mode and effect analysis (FMEA) to enhance maintenance planning. Comput. Ind. (2021). https://doi.org/10.1016/j.compind.2021.103451

    Article  Google Scholar 

  28. P.A.A. Garcia, R. Schirru, P.F.F. Melo, A fuzzy data envelopment analysis approach for FMEA. Prog. Nucl. Energy. 46, 359–373 (2005). https://doi.org/10.1016/j.pnucene.2005.03.016

    Article  Google Scholar 

  29. J.J. George, V.R. Renjith, P. George, A.S. George, Application of fuzzy failure mode effect and criticality analysis on unloading facility of LNG terminal. J. Loss Prev. Process Ind. 61, 104–113 (2019). https://doi.org/10.1016/j.jlp.2019.06.009

    Article  Google Scholar 

  30. S.S. Grossel, Book review: guidelines for mechanical integrity systems, the center for chemical process safety. J. Loss Prev. Process Ind. 20, 108–110 (2007). https://doi.org/10.1016/j.jlp.2006.10.001

    Article  Google Scholar 

  31. L. Guo, J. Gao, J. Yang, J. Kang, Criticality evaluation of petrochemical equipment based on fuzzy comprehensive evaluation and a BP neural network. J. Loss Prev. Process Ind. 22, 469–476 (2009). https://doi.org/10.1016/j.jlp.2009.03.003

    Article  CAS  Google Scholar 

  32. X. Guo, J. Ji, F. Khan, L. Ding, Y. Yang, Fuzzy bayesian network based on an improved similarity aggregation method for risk assessment of storage tank accident. Process Saf. Environ. Prot. 149, 817–830 (2021). https://doi.org/10.1016/j.psep.2021.03.017

    Article  CAS  Google Scholar 

  33. R.D. Gupta, D. Kundu, Generalized exponential distribution: existing results and some recent developments. Journal of Statistical Planning and Inference. 137, 3537–3547 (2007). https://doi.org/10.1016/j.jspi.2007.03.030

    Article  Google Scholar 

  34. H. Hammoum, K. Bouzelha, H.A. Aider, N.E. Hannachi, Tanks criticality assessment by the dependability method: a case study. Eng. Fail. Anal. 41, 10–22 (2014). https://doi.org/10.1016/j.engfailanal.2013.07.016

    Article  Google Scholar 

  35. B.M. Hsu, M.H. Shu, B.S. Chen, Evaluating lifetime performance for the Pareto model with censored and imprecise information. J. Stat. Comput. Simul. 81, 1817–1833 (2011). https://doi.org/10.1080/00949655.2010.506439

    Article  Google Scholar 

  36. J.M. Juran, Juran’s Quality Control Handbook. (McGraw-Hill Inc, London, 1988)

    Google Scholar 

  37. J. Kang, W. Liang, L. Zhang, Z. Lu, D. Liu, W. Yin, G. Zhang, A new risk evaluation method for oil storage tank zones based on the theory of two types of hazards. J. Loss Prev. Process Ind. 29, 267–276 (2014). https://doi.org/10.1016/j.jlp.2014.03.007

    Article  CAS  Google Scholar 

  38. F. Keynia, M. Mirhosseini, A. Heydari, A. Fekih, A budget allocation and programming-based RCM approach to improve the reliability of power distribution networks. Energy Rep. 8, 5591–5602 (2022). https://doi.org/10.1016/j.egyr.2022.04.029

    Article  Google Scholar 

  39. J.S. Kim, D.H. An, S.Y. Lee, A failure analysis of fillet joint cracking in an oil storage tank. J. Loss Prev. Process Ind. 22, 845–849 (2009). https://doi.org/10.1016/j.jlp.2009.08.014

    Article  CAS  Google Scholar 

  40. L.N. Komariah, S. Arita, B.E. Prianda, T.K. Dewi, Technical assessment of biodiesel storage tank: a corrosion case study. J. King Saud Univ. Eng. Sci. (2021). https://doi.org/10.1016/j.jksues.2021.03.016

    Article  Google Scholar 

  41. J.F. Lawless, Statistical Models and Methods for Lifetime Data. (Wiley InterScience, Washington, 2003) https://doi.org/10.1002/9781118033005

    Book  Google Scholar 

  42. A.J. Lemonte, A new exponential-type distribution with constant, decreasing, increasing, upside-down bathtub and bathtub-shaped failure rate function. Comput. Stat. Data Anal. 62, 149–170 (2013). https://doi.org/10.1016/j.csda.2013.01.011

    Article  Google Scholar 

  43. D. Li, J. Gao, Study and application of reliability-centered maintenance considering radical maintenance. J. Loss Prev. Process Ind. 23, 622–629 (2010). https://doi.org/10.1016/j.jlp.2010.06.008

    Article  CAS  Google Scholar 

  44. H. Li, M. Yazdi, Developing failure modes and effect analysis on offshore wind turbines using two-stage optimization probabilistic linguistic preference relations, in Advanced Decision-Making Methods and Applications in System Safety and Reliability Problems: Approaches, Case Studies, Multi-criteria Decision-Making, Multi-objective Decision-Making, Fuzzy Risk-Based Models. Springer International Publishing, Cham (2022) https://doi.org/10.1007/978-3-031-07430-1_4

  45. W. Limin, Fault tree analysis for oil tank fire and explosion, in IEEE International Conference on Emergency Management and Management Sciences (ICEMMS), Langfang, Hebei Province, China (2010) https://doi.org/10.1109/ICEMMS.2010.5563394

  46. C. Matthews, Tank repairs and alterations, A Quick Guide to API 653 Certified Storage Tank Inspector Syllabus, Woodhead Publishing, 2011. https://doi.org/10.1533/9780857095275.157

  47. J. Menčík, Reliability of systems, in J. Mencik ed. Concise Reliability for Engineers. IntechOpen, Rijeka, Croatia (2016) https://doi.org/10.5772/62358

  48. M.F. Milazzo, G. Ancione, P. Bragatto, E. Proverbio, A probabilistic approach for the estimation of the residual useful lifetime of atmospheric storage tanks in oil industry. J. Loss Prev. Process Ind. (2022). https://doi.org/10.1016/j.jlp.2022.104781

    Article  Google Scholar 

  49. N. Z. Milovanović, R. L. Papić, Z. S. Milovanović, V. Z. Janičić-Milovanović, S. R. Dumonjić-Milovanović, D. J. Branković, Qualitative analysis in the reliability assessment of the steam turbine plant, in Kumar, A. A. R., M. ed. The Handbook of Reliability, Maintenance, and System Safety through Mathematical Modeling. Academic Press (2021) https://doi.org/10.1016/B978-0-12-819582-6.00008-3

  50. J. Moubray, Reliability Centered Maintenance. (Industrial Press Inc, New York, 1997) https://doi.org/10.1002/qre.4680080114

    Book  Google Scholar 

  51. S. Ni, Y. Tang, G. Wang, L. Yang, B. Lei, Z. Zhang, Risk identification and quantitative assessment method of offshore platform equipment. Energy Rep. 8, 7219–7229 (2022). https://doi.org/10.1016/j.egyr.2022.05.159

    Article  Google Scholar 

  52. M. Ohring, L. Kasprzak, The mathematics of failure and reliability, in M. Ohring, L. Kasprzak, eds. Reliability and failure of electronic materials and devices. 2 ed. Boston, 2015 Academic Press. https://doi.org/10.1016/B978-0-12-088574-9.00004-5

  53. A. Ozdemir, E. D. Kuldasli, RCM Application for Turkish National power transmission system, 11th International Conference on Probabilistic Methods Applied to Power Systems (PMAPS), 2010 Istanbul, Turkey. IEEE. https://doi.org/10.1109/PMAPS.2010.5528989

  54. D. Panchal, D. Kumar, Integrated framework for behaviour analysis in a process plant. J. Loss Prev. Process Ind. 40, 147–161 (2016). https://doi.org/10.1016/j.jlp.2015.12.021

    Article  Google Scholar 

  55. H. Pasman, W. Rogers, How trustworthy are risk assessment results, and what can be done about the uncertainties they are plagued with? J. Loss Prev. Process Ind. 55, 162–177 (2018). https://doi.org/10.1016/j.jlp.2018.06.004

    Article  Google Scholar 

  56. J.F.W. Peeters, R.J.I. Basten, T. Tinga, Improving failure analysis efficiency by combining FTA and FMEA in a recursive manner. Reliab. Eng. Syst. Saf. 172, 36–44 (2018). https://doi.org/10.1016/j.ress.2017.11.024

    Article  Google Scholar 

  57. L. Pelissero, Mechanical Integrity of Atmospheric Tanks 2nd International Conference on System Reliability and Safety, 2017 Italy. https://doi.org/10.1109/ICSRS.2017.8272841

  58. P. Pougnet, F. Bayle, H. Maanane, P. R. Dahoo, Reliability prediction of embedded electronic systems: the FIDES guide, in E. H. Abdelkhalak, P. Pougnet, ed. Embedded Mechatronic Systems. 2 edn.: Elsevier, Amsterdam. https://doi.org/10.1016/B978-1-78548-189-5.50008-2.

  59. Y. Redutskiy, C.M. Camitz-Leidland, A. Vysochyna, K.T. Anderson, M. Balycheva, Safety systems for the oil and gas industrial facilities: design, maintenance policy choice, and crew scheduling. Reliab. Eng. Syst. Saf. (2021). https://doi.org/10.1016/j.ress.2021.107545

    Article  Google Scholar 

  60. V.R. Renjith, M.J. Kalathil, P.H. Kumar, D. Madhavan, Fuzzy FMECA (failure mode effect and criticality analysis) of LNG storage facility. J. Loss Prev. Process Ind. 56, 537–547 (2018). https://doi.org/10.1016/j.jlp.2018.01.002

    Article  CAS  Google Scholar 

  61. C. Riverol, V. Pilipovik, A reliability prediction methodology based on improved radial basis function neural network (RBFNN): a condensate light crude oil stabilization facility as case study. Saf. Reliab. 40, 157–164 (2021). https://doi.org/10.1080/09617353.2021.1989227

    Article  Google Scholar 

  62. M. Shafiee, T. Elusakin, E. Enjema, Subsea blowout preventer (BOP): design, reliability, testing, deployment, and operation and maintenance challenges. J. Loss Prev. Process Ind. (2020). https://doi.org/10.1016/j.jlp.2020.104170

    Article  Google Scholar 

  63. M.M. Shahri, A.E. Jahromi, M. Houshmand, Failure mode and effect analysis using an integrated approach of clustering and MCDM under pythagorean fuzzy environment. J. Loss Prev. Process Ind. (2021). https://doi.org/10.1016/j.jlp.2021.104591

    Article  Google Scholar 

  64. J. Shuai, K. Han, X. Xu, Risk-based inspection for large-scale crude oil tanks. J. Loss Prev. Process Ind. 25, 166–175 (2012). https://doi.org/10.1016/j.jlp.2011.08.004

    Article  Google Scholar 

  65. Y. Tang, Q. Liu, J. Jing, Y. Yang, Z. Zou, A framework for identification of maintenance significant items in reliability-centered maintenance. Energy. 118, 1295–1303 (2017). https://doi.org/10.1016/j.energy.2016.11.011

    Article  Google Scholar 

  66. M. Villarini, V. Cesarotti, L. Alfonsi, V. Introna, Optimization of photovoltaic maintenance plan by means of a FMEA approach based on real data. Energy Convers. Manage. 152, 1–12 (2017). https://doi.org/10.1016/j.enconman.2017.08.090

    Article  Google Scholar 

  67. C.R. Vishnu, V. Regikumar, Reliability Based Maintenance Strategy Selection in Process Plants: A Case Study. Procedia Technology 25, 1080–1087 (2016). https://doi.org/10.1016/j.protcy.2016.08.211.

  68. Y. Wang, G. Cheng, H. Hu, W. Wu, development of a risk-based maintenance strategy using FMEA for a continuous catalytic reforming plant. J. Loss Prev. Process Ind. 25, 958–965 (2012). https://doi.org/10.1016/j.jlp.2012.05.009

    Article  CAS  Google Scholar 

  69. N. Williard, S. Mathew, Book review: effective FMEAs. Microelectron. Reliab. (2012). https://doi.org/10.1016/j.microrel.2012.05.004

    Article  Google Scholar 

  70. C.W. Wu, M.H. Shu, Y.N. Chang, Variable-sampling plans based on lifetime-performance index under exponential distribution with censoring and its extensions. Appl. Math. Model. 55, 81–93 (2018). https://doi.org/10.1016/j.apm.2017.10.027

    Article  Google Scholar 

  71. Z. Wu, L. Hou, S. Wu, X. Wu, F. Liu, The time-to-failure assessment of large crude oil storage tank exposed to pool fire. Fire Saf. J. 117, 1–13 (2020). https://doi.org/10.1016/j.firesaf.2020.103192

    Article  CAS  Google Scholar 

  72. M. Xie, Y. Tang, T.N. Goh, A modified weibull extension with bathtub-shaped failure rate function. Reliab. Eng. Syst. Saf. 76, 279–285 (2002). https://doi.org/10.1016/S0951-8320(02)00022-4

    Article  Google Scholar 

  73. M. Yazdi, S. Daneshvar, H. Setareh, An extension to fuzzy developed failure mode and effects analysis (FDFMEA) application for aircraft landing system. Saf. Sci. 98, 113–123 (2017). https://doi.org/10.1016/j.ssci.2017.06.009

    Article  Google Scholar 

  74. A. Yu, H. Liu, L. Zhang, Y. Chen, A new data envelopment analysis-based model for failure mode and effect analysis with heterogeneous information. Comput. Ind. Eng. (2021). https://doi.org/10.1016/j.cie.2021.107350

    Article  Google Scholar 

  75. Y. Zennir, A. B. Ahmed, E. A. Mechhoud, Safety study of the industrial systems with fmea(c): application to the TK102 Storage Tank, in European Control Conference, 2014 Strasbourg, France. IEEE, pp. 2804–2809. https://doi.org/10.1109/ECC.2014.6862345

  76. Y. Zhang, X. Liu, J. Lai, Y. Wei, J. Luo, Corrosion fatigue life prediction of crude oil storage tank via improved equivalent initial flaw size. Theor. Appl. Fract. Mech. (2021). https://doi.org/10.1016/j.tafmec.2021.103023

    Article  Google Scholar 

  77. F. Zheng, M. Zhang, J. Song, F.Z. Chen, Analysis on risk of multi—factor disaster and disaster control in oil and gas storage tank. Procedia Eng. 211, 1058–1064 (2018). https://doi.org/10.1016/j.proeng.2017.12.110

    Article  Google Scholar 

  78. R. Zinke, J. Melnychuk, F. Köhler, U. Krause, Quantitative risk assessment of emissions from external floating roof tanks during normal operation and in case of damages using bayesian networks. Reliab. Eng. Syst. Saf. (2020). https://doi.org/10.1016/j.ress.2020.106826

    Article  Google Scholar 

  79. E. Zio, M. Fan, Z. Zeng, R. Kang, Application of reliability technologies in civil aviation: lessons learnt and perspectives. Chin. J. Aeronaut. 32, 143–158 (2019). https://doi.org/10.1016/j.cja.2018.05.014

    Article  Google Scholar 

  80. S. Zou, Y. Kuang, D. Tang, Z. Guo, S. Xu, Risk Analysis of High Level Radioactive Waste Storage Tank based on HAZOP. Ann. Nucl. Energy. 119, 106–116 (2018). https://doi.org/10.1016/j.anucene.2018.04.021

    Article  CAS  Google Scholar 

Download references

Acknowledgment

The authors sincerely thank Dr. Muhammad A. Sheikh retired as a Reader from The University of Manchester, UK, for his critical discussion on modeling results and reading during manuscript preparation.

Author information

Authors and Affiliations

  1. Department of Automotive and Marine Engineering, NED University of Engineering and Technology, Karachi, 75270, Pakistan

    Faraz Akbar

  2. Mechanical Engineering Department, NED University of Engineering and Technology, Karachi, 75270, Pakistan

    Sarah Zaki

Authors
  1. Faraz Akbar
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sarah Zaki
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

FA was involved in research methodology, writing—reviewing and editing, industrial data support, reliability analysis and supervision. SZ was responsible for reviewing the literature, writing the original draft, and reviewing and editing the manuscript.

Corresponding author

Correspondence to Faraz Akbar.

Ethics declarations

Conflict of interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Additional information

Publisher's Note

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

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Akbar, F., Zaki, S. Fixed-Roof Hydrocarbon Oil Storage Tank: An Approach to Reliability Engineering Tools. J Fail. Anal. and Preven. 23, 2044–2064 (2023). https://doi.org/10.1007/s11668-023-01733-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11668-023-01733-5

Keywords

Search

Navigation