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Customized risk assessment in military shipbuilding

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  • Crispim, José
  • Fernandes, Jorge
  • Rego, Nazaré

Abstract

This paper describes a customized risk assessment framework to be applied in military shipbuilding projects. The framework incorporates the Delphi method with visual diagrams, Bayesian Networks (BN) and the expression of expert opinions through linguistic variables. Noisy-OR and Leak Canonical models are used to determine the conditional probabilities of the BN model. The approach can easily be adapted for other shipbuilding construction projects. The visual diagrams that support the Delphi questionnaire favor the comprehensive visualization of the interdependencies between risks, causes, risks and causes, and risks and effects. The applicability of the framework is illustrated through the assessment of risk of two real military shipbuilding projects. This assessment includes a sensitivity analysis that is useful to prioritize mitigation actions. In the two cases studies, the risks with higher probability of occurrence were failures or errors in production, of the contracted, in the requirements, and in planning. The results of the sensitivity analysis showed that a set of mitigation actions directed at relatively easily controllable causes would have achieved important reductions in risk probabilities.

Suggested Citation

  • Crispim, José & Fernandes, Jorge & Rego, Nazaré, 2020. "Customized risk assessment in military shipbuilding," Reliability Engineering and System Safety, Elsevier, vol. 197(C).
    • Handle: RePEc:eee:reensy:v:197:y:2020:i:c:s0951832018313930
    DOI: 10.1016/j.ress.2020.106809
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    as
    1. Patrick Zou & Jie Li, 2010. "Risk identification and assessment in subway projects: case study of Nanjing Subway Line 2," Construction Management and Economics, Taylor & Francis Journals, vol. 28(12), pages 1219-1238.
    2. Venkatesh, V.G. & Rathi, Snehal & Patwa, Sriyans, 2015. "Analysis on supply chain risks in Indian apparel retail chains and proposal of risk prioritization model using Interpretive structural modeling," Journal of Retailing and Consumer Services, Elsevier, vol. 26(C), pages 153-167.
    3. Albert Chan & Esther Yung & Patrick Lam & C. M. Tam & S. O. Cheung, 2001. "Application of Delphi method in selection of procurement systems for construction projects," Construction Management and Economics, Taylor & Francis Journals, vol. 19(7), pages 699-718.
    4. N. Carbonara & N. Costantino & L. Gunnigan & R. Pellegrino, 2015. "Risk Management in Motorway PPP Projects: Empirical-based Guidelines," Transport Reviews, Taylor & Francis Journals, vol. 35(2), pages 162-182, March.
    5. Christiansen, Ulrik & Thrane, Sof, 2014. "The prose of action: The micro dynamics of reporting on emerging risks in operational risk management," Scandinavian Journal of Management, Elsevier, vol. 30(4), pages 427-443.
    6. Rowe, Gene & Wright, George, 1999. "The Delphi technique as a forecasting tool: issues and analysis," International Journal of Forecasting, Elsevier, vol. 15(4), pages 353-375, October.
    7. Zhang, Limao & Wu, Xianguo & Skibniewski, Miroslaw J. & Zhong, Jingbing & Lu, Yujie, 2014. "Bayesian-network-based safety risk analysis in construction projects," Reliability Engineering and System Safety, Elsevier, vol. 131(C), pages 29-39.
    8. Abderrahmane Sokri & Ahmed Ghanmi, 2017. "Cost risk analysis and learning curve in the military shipbuilding sector," International Journal of Data Analysis Techniques and Strategies, Inderscience Enterprises Ltd, vol. 9(4), pages 300-313.
    9. Behzad Esmaeili & Matthew Hallowell, 2013. "Integration of safety risk data with highway construction schedules," Construction Management and Economics, Taylor & Francis Journals, vol. 31(6), pages 528-541, June.
    10. Stefan Creemers & Erik Demeulemeester & Stijn Vonder, 2014. "A new approach for quantitative risk analysis," Annals of Operations Research, Springer, vol. 213(1), pages 27-65, February.
    11. Ibsen Chivatá Cárdenas & Saad S.H. Al‐jibouri & Johannes I.M. Halman & Frits A. van Tol, 2013. "Capturing and Integrating Knowledge for Managing Risks in Tunnel Works," Risk Analysis, John Wiley & Sons, vol. 33(1), pages 92-108, January.
    12. Ibsen Chivatá Cárdenas & Saad S. H. Al‐Jibouri & Johannes I. M. Halman & Wim van de Linde & Frank Kaalberg, 2014. "Using Prior Risk‐Related Knowledge to Support Risk Management Decisions: Lessons Learnt from a Tunneling Project," Risk Analysis, John Wiley & Sons, vol. 34(10), pages 1923-1943, October.
    13. Martina E. Murphy & Srinath Perera & George Heaney, 2015. "Innovation management model: a tool for sustained implementation of product innovation into construction projects," Construction Management and Economics, Taylor & Francis Journals, vol. 33(3), pages 209-232, March.
    14. Boa Zhang Lu & Alan S. T. Tang, 2000. "China shipbuilding management challenges in the 1980s," Maritime Policy & Management, Taylor & Francis Journals, vol. 27(1), pages 71-78.
    15. Jones, B. & Jenkinson, I. & Yang, Z. & Wang, J., 2010. "The use of Bayesian network modelling for maintenance planning in a manufacturing industry," Reliability Engineering and System Safety, Elsevier, vol. 95(3), pages 267-277.
    16. Markmann, Christoph & Darkow, Inga-Lena & von der Gracht, Heiko, 2013. "A Delphi-based risk analysis — Identifying and assessing future challenges for supply chain security in a multi-stakeholder environment," Technological Forecasting and Social Change, Elsevier, vol. 80(9), pages 1815-1833.
    17. Sherong Zhang & Bo Sun & Lei Yan & Chao Wang, 2013. "Risk identification on hydropower project using the IAHP and extension of TOPSIS methods under interval-valued fuzzy environment," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 65(1), pages 359-373, January.
    18. Zio, E., 2018. "The future of risk assessment," Reliability Engineering and System Safety, Elsevier, vol. 177(C), pages 176-190.
    19. Magdy M. Hussein, 2010. "Corporate social responsibility: finding the middle ground," Social Responsibility Journal, Emerald Group Publishing Limited, vol. 6(3), pages 420-432, August.
    20. Limao Zhang & Xianguo Wu & Yawei Qin & Miroslaw J. Skibniewski & Wenli Liu, 2016. "Towards a Fuzzy Bayesian Network Based Approach for Safety Risk Analysis of Tunnel‐Induced Pipeline Damage," Risk Analysis, John Wiley & Sons, vol. 36(2), pages 278-301, February.
    21. Schjaer-Jacobsen, Hans, 2002. "Representation and calculation of economic uncertainties: Intervals, fuzzy numbers, and probabilities," International Journal of Production Economics, Elsevier, vol. 78(1), pages 91-98, July.
    22. Othonas Zacharias & Eleni Panou & D. Th. Askounis & Aikaterini Vassilikopoulou, 2014. "Project Risk Ranking In Large-Scale Programs: A Fuzzy Set Based Approach," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 31(03), pages 1-22.
    23. Wu, Wei-Shing & Yang, Chen-Feng & Chang, Jung-Chuan & Château, Pierre-Alexandre & Chang, Yang-Chi, 2015. "Risk assessment by integrating interpretive structural modeling and Bayesian network, case of offshore pipeline project," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 515-524.
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    2. Chen, Yinuo & Tian, Zhigang & He, Rui & Wang, Yifei & Xie, Shuyi, 2023. "Discovery of potential risks for the gas transmission station using monitoring data and the OOBN method," Reliability Engineering and System Safety, Elsevier, vol. 232(C).

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