IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i18p7294-d409524.html
   My bibliography  Save this article

Analysis and Characterization of Risk Methodologies Applied to Industrial Parks

Author

Listed:
  • Martin Folch-Calvo

    (Manufacturing and Construction Engineering Department, National University of Distance Education, 28040 Madrid, Spain)

  • Francisco Brocal-Fernández

    (Department of Physics, University of Alicante, 03690 Alicante, Spain)

  • Cristina González-Gaya

    (Manufacturing and Construction Engineering Department, National University of Distance Education, 28040 Madrid, Spain)

  • Miguel A. Sebastián

    (Manufacturing and Construction Engineering Department, National University of Distance Education, 28040 Madrid, Spain)

Abstract

It is important to evaluate the risks in industrial parks and their processes due to the consequences of major accidents and especially the domino effect. Scientific works present a wide possibility of models to deal with these situations. In this work, based on the information extracted from the scientific literature, six groups of risk methodologies are defined, analyzed, and characterized with methods that cover the standards, preventive, probabilistic, traditional, modern, and dynamic evaluation that are applied or could be used in industrial parks. It also tries to achieve the objective of determining which are more appropriate if the possible situations and causes that can produce an accident are taken into account, identifying and evaluating them with characteristics of simultaneity and immediacy, determining the probability of an accident occurring with sufficient advance in time to avoid it under the use of a working operational procedure. There is no definitive methodology, and it is necessary that they complement each other, but considering the proposed objective, the integrated application of traditional methodologies together with the management of safety barriers, the dynamic evaluation of risks, and the inclusion of machine learning systems could fulfill the proposed objective.

Suggested Citation

  • Martin Folch-Calvo & Francisco Brocal-Fernández & Cristina González-Gaya & Miguel A. Sebastián, 2020. "Analysis and Characterization of Risk Methodologies Applied to Industrial Parks," Sustainability, MDPI, vol. 12(18), pages 1-35, September.
  • Handle: RePEc:gam:jsusta:v:12:y:2020:i:18:p:7294-:d:409524
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/18/7294/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/12/18/7294/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Khakzad, Nima & Khan, Faisal & Amyotte, Paul, 2011. "Safety analysis in process facilities: Comparison of fault tree and Bayesian network approaches," Reliability Engineering and System Safety, Elsevier, vol. 96(8), pages 925-932.
    2. Gianpaolo Di Bona & Alessandro Silvestri & Antonio Forcina & Antonella Petrillo, 2018. "Total efficient risk priority number (TERPN): a new method for risk assessment," Journal of Risk Research, Taylor & Francis Journals, vol. 21(11), pages 1384-1408, November.
    3. Yang, Ruochen & Khan, Faisal & Neto, Eugenio Turco & Rusli, Riza & Ji, Jie, 2020. "Could pool fire alone cause a domino effect?," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    4. Khakzad, Nima & Landucci, Gabriele & Cozzani, Valerio & Reniers, Genserik & Pasman, Hans, 2018. "Cost-effective fire protection of chemical plants against domino effects," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 412-421.
    5. Enrico Zio, 2013. "The Monte Carlo Simulation Method for System Reliability and Risk Analysis," Springer Series in Reliability Engineering, Springer, edition 127, number 978-1-4471-4588-2, December.
    6. Enrico Zio, 2013. "System Reliability and Risk Analysis by Monte Carlo Simulation," Springer Series in Reliability Engineering, in: The Monte Carlo Simulation Method for System Reliability and Risk Analysis, edition 127, chapter 0, pages 59-81, Springer.
    7. Bjerga, Torbjørn & Aven, Terje & Zio, Enrico, 2016. "Uncertainty treatment in risk analysis of complex systems: The cases of STAMP and FRAM," Reliability Engineering and System Safety, Elsevier, vol. 156(C), pages 203-209.
    8. Hemmatian, Behrouz & Planas, Eulà lia & Casal, Joaquim, 2015. "Fire as a primary event of accident domino sequences: The case of BLEVE," Reliability Engineering and System Safety, Elsevier, vol. 139(C), pages 141-148.
    9. Alileche, Nassim & Cozzani, Valerio & Reniers, Genserik & Estel, Lionel, 2015. "Thresholds for domino effects and safety distances in the process industry: A review of approaches and regulations," Reliability Engineering and System Safety, Elsevier, vol. 143(C), pages 74-84.
    10. Nguyen, Son & Chen, Peggy Shu-Ling & Du, Yuquan & Shi, Wenming, 2019. "A quantitative risk analysis model with integrated deliberative Delphi platform for container shipping operational risks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 129(C), pages 203-227.
    11. Syed, Zaki & Lawryshyn, Yuri, 2020. "Risk analysis of an underground gas storage facility using a physics-based system performance model and Monte Carlo simulation," Reliability Engineering and System Safety, Elsevier, vol. 199(C).
    12. Liu, Zhe & Adams, Michelle & Cote, Raymond P. & Geng, Yong & Ren, Jingzheng & Chen, Qinghua & Liu, Weili & Zhu, Xuesong, 2018. "Co-benefits accounting for the implementation of eco-industrial development strategies in the scale of industrial park based on emergy analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1522-1529.
    13. Bier, Vicki M. & Yi, Woojune, 1995. "A Bayesian method for analyzing dependencies in precursor data," International Journal of Forecasting, Elsevier, vol. 11(1), pages 25-41, March.
    14. Khakzad, Nima & Landucci, Gabriele & Reniers, Genserik, 2017. "Application of dynamic Bayesian network to performance assessment of fire protection systems during domino effects," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 232-247.
    15. Hou, Lei & Wu, Xingguang & Wu, Zhuang & Wu, Shouzhi, 2020. "Pattern identification and risk prediction of domino effect based on data mining methods for accidents occurred in the tank farm," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    16. Paltrinieri, Nicola & Tugnoli, Alessandro & Cozzani, Valerio, 2015. "Hazard identification for innovative LNG regasification technologies," Reliability Engineering and System Safety, Elsevier, vol. 137(C), pages 18-28.
    17. Enrico Zio, 2013. "Monte Carlo Simulation: The Method," Springer Series in Reliability Engineering, in: The Monte Carlo Simulation Method for System Reliability and Risk Analysis, edition 127, chapter 0, pages 19-58, Springer.
    18. Rachman, Andika & Ratnayake, R.M. Chandima, 2019. "Machine learning approach for risk-based inspection screening assessment," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 518-532.
    19. Churchwell, Jared S. & Zhang, Katherine S. & Saleh, Joseph H., 2018. "Epidemiology of helicopter accidents: Trends, rates, and covariates," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 373-384.
    20. Konstandinidou, Myrto & Nivolianitou, Zoe & Kiranoudis, Chris & Markatos, Nikolaos, 2006. "A fuzzy modeling application of CREAM methodology for human reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 91(6), pages 706-716.
    21. Singh, Kritika & Maiti, J, 2020. "A novel data mining approach for analysis of accident paths and performance assessment of risk control systems," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    22. Khakzad, Nima, 2015. "Application of dynamic Bayesian network to risk analysis of domino effects in chemical infrastructures," Reliability Engineering and System Safety, Elsevier, vol. 138(C), pages 263-272.
    23. Enrico Zio, 2013. "System Reliability and Risk Analysis," Springer Series in Reliability Engineering, in: The Monte Carlo Simulation Method for System Reliability and Risk Analysis, edition 127, chapter 0, pages 7-17, Springer.
    24. Janssens, Jochen & Talarico, Luca & Reniers, Genserik & Sörensen, Kenneth, 2015. "A decision model to allocate protective safety barriers and mitigate domino effects," Reliability Engineering and System Safety, Elsevier, vol. 143(C), pages 44-52.
    25. Nima Khakzad & Faisal Khan & Paul Amyotte & Valerio Cozzani, 2014. "Risk Management of Domino Effects Considering Dynamic Consequence Analysis," Risk Analysis, John Wiley & Sons, vol. 34(6), pages 1128-1138, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Katarina Buganova & Maria Luskova & Jozef Kubas & Michal Brutovsky & Jaroslav Slepecky, 2021. "Sustainability of Business through Project Risk Identification with Use of Expert Estimates," Sustainability, MDPI, vol. 13(11), pages 1-17, June.
    2. Maria Polorecka & Jozef Kubas & Pavel Danihelka & Katarina Petrlova & Katarina Repkova Stofkova & Katarina Buganova, 2021. "Use of Software on Modeling Hazardous Substance Release as a Support Tool for Crisis Management," Sustainability, MDPI, vol. 13(1), pages 1-15, January.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Khakzad, Nima, 2023. "A methodology based on Dijkstra's algorithm and mathematical programming for optimal evacuation in process plants in the event of major tank fires," Reliability Engineering and System Safety, Elsevier, vol. 236(C).
    2. Kim, Hyeonmin & Kim, Jung Taek & Heo, Gyunyoung, 2018. "Failure rate updates using condition-based prognostics in probabilistic safety assessments," Reliability Engineering and System Safety, Elsevier, vol. 175(C), pages 225-233.
    3. Guo, Xiaoxue & Ding, Long & Ji, Jie & Cozzani, Valerio, 2022. "A cost-effective optimization model of safety investment allocation for risk reduction of domino effects," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    4. Guowang Meng & Hongle Li & Bo Wu & Guangyang Liu & Huazheng Ye & Yiming Zuo, 2023. "Prediction of the Tunnel Collapse Probability Using SVR-Based Monte Carlo Simulation: A Case Study," Sustainability, MDPI, vol. 15(9), pages 1-21, April.
    5. Michael Saidani & Alissa Kendall & Bernard Yannou & Yann Leroy & François Cluzel, 2019. "Closing the loop on platinum from catalytic converters: Contributions from material flow analysis and circularity indicators," Post-Print hal-02094798, HAL.
    6. Michele Compare & Francesco Di Maio & Enrico Zio & Fausto Carlevaro & Sara Mattafirri, 2016. "Improving scheduled maintenance by missing data reconstruction: A double-loop Monte Carlo approach," Journal of Risk and Reliability, , vol. 230(5), pages 502-511, October.
    7. Chiacchio, Ferdinando & D’Urso, Diego & Famoso, Fabio & Brusca, Sebastian & Aizpurua, Jose Ignacio & Catterson, Victoria M., 2018. "On the use of dynamic reliability for an accurate modelling of renewable power plants," Energy, Elsevier, vol. 151(C), pages 605-621.
    8. Salomon, Julian & Winnewisser, Niklas & Wei, Pengfei & Broggi, Matteo & Beer, Michael, 2021. "Efficient reliability analysis of complex systems in consideration of imprecision," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    9. Di Maio, Francesco & Pettorossi, Chiara & Zio, Enrico, 2023. "Entropy-driven Monte Carlo simulation method for approximating the survival signature of complex infrastructures," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    10. Khakzad, Nima, 2021. "Optimal firefighting to prevent domino effects: Methodologies based on dynamic influence diagram and mathematical programming," Reliability Engineering and System Safety, Elsevier, vol. 212(C).
    11. Misuri, Alessio & Landucci, Gabriele & Cozzani, Valerio, 2021. "Assessment of risk modification due to safety barrier performance degradation in Natech events," Reliability Engineering and System Safety, Elsevier, vol. 212(C).
    12. Wang, Fan & Li, Heng, 2018. "System reliability under prescribed marginals and correlations: Are we correct about the effect of correlations?," Reliability Engineering and System Safety, Elsevier, vol. 173(C), pages 94-104.
    13. Tito G. Amaral & Vitor Fernão Pires & Armando Cordeiro & Daniel Foito & João F. Martins & Julia Yamnenko & Tetyana Tereschenko & Liudmyla Laikova & Ihor Fedin, 2023. "Incipient Fault Diagnosis of a Grid-Connected T-Type Multilevel Inverter Using Multilayer Perceptron and Walsh Transform," Energies, MDPI, vol. 16(6), pages 1-18, March.
    14. Zhang, Hanxiao & Sun, Muxia & Li, Yan-Fu, 2022. "Reliability–redundancy allocation problem in multi-state flow network: Minimal cut-based approximation scheme," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    15. Tosoni, E. & Salo, A. & Govaerts, J. & Zio, E., 2019. "Comprehensiveness of scenarios in the safety assessment of nuclear waste repositories," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 561-573.
    16. Penttinen, Jussi-Pekka & Niemi, Arto & Gutleber, Johannes & Koskinen, Kari T. & Coatanéa, Eric & Laitinen, Jouko, 2019. "An open modelling approach for availability and reliability of systems," Reliability Engineering and System Safety, Elsevier, vol. 183(C), pages 387-399.
    17. Rocco, Claudio M. & Moronta, José & Ramirez-Marquez, José E. & Barker, Kash, 2017. "Effects of multi-state links in network community detection," Reliability Engineering and System Safety, Elsevier, vol. 163(C), pages 46-56.
    18. Compare, Michele & Bellani, Luca & Zio, Enrico, 2019. "Optimal allocation of prognostics and health management capabilities to improve the reliability of a power transmission network," Reliability Engineering and System Safety, Elsevier, vol. 184(C), pages 164-180.
    19. Babykina, Génia & Brînzei, Nicolae & Aubry, Jean-François & Deleuze, Gilles, 2016. "Modeling and simulation of a controlled steam generator in the context of dynamic reliability using a Stochastic Hybrid Automaton," Reliability Engineering and System Safety, Elsevier, vol. 152(C), pages 115-136.
    20. Compare, Michele & Bellani, Luca & Zio, Enrico, 2017. "Reliability model of a component equipped with PHM capabilities," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 4-11.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:12:y:2020:i:18:p:7294-:d:409524. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.