PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Tytuł artykułu

An algorithmic tool for supporting risk and root-cause analysis of critical incidents in Baltic Sea Region ports

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This paper is both a summarization and extension of [6] and [7], where a stochastic model of interacting operations carried out in a generic Baltic Sea Region port was proposed and analyzed. Each operation involves a number of possible unwanted events (critical incidents) whose instances occur randomly and can cause instances of other events affecting this or other operations. This can lead to a cause-effect chain of events affecting one or multiple operations. The model presented in [6] is somewhat complex, therefore it was downgraded to a simpler, application-oriented version demonstrated in [7], where an algorithm computing the risks of critical incidents is constructed and then applied to a real-life example. The current paper, apart from presenting a method of computing the risks of critical incidents, occurring by themselves or resulting from the cascade effect, also features a method of root-cause analysis of such incidents. First, the formulas for the root-cause probabilities are derived, where such a probability quantifies the likelihood that a critical incident occurring in step h of a cascade was caused by another incident that initiated this cascade. Second, an algorithm computing the root-cause probabilities, based on the derived formulas, is constructed. This algorithm is illustrated by its application to the example given in [7]. The presented results can be used as a tool for fault propagation analysis and fault diagnosis applied not only to a port environment, but to any complex industrial system.
Rocznik
Strony
127--136
Opis fizyczny
Bibliogr. 9 poz.
Twórcy
  • Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland
Bibliografia
  • [1] Bielecki, T.R., Vidozzi, A., Vidozzi, L. & Jakubowski, J. (2008). Study of dependence for some stochastic processes. Stochastic Analysis and Applications 26, 1-16.
  • [2] Cai, B., Huang, L., Xie, M. (2017). Bayesian networks in fault diagnosis. IEEE Transactions on Industrial Informatics 13(5), 2227-2240.
  • [3] Dong, H. & Cui, L. (2016). System Reliability Under Cascading Failure Models. IEEE Transactions on Reliability 65, 929-940.
  • [4] Hu, J., Zhang, L., Cai, Z., Wang, Y., Wang, A. (2015). Fault propagation behavior study and root cause reasoning with dynamic Bayesian network based framework. Process Safety and Environmental Protection 97, 25-36.
  • [5] Iyer, S. M., Marvin K. Nakayama & Gerbessiotis A. V. (2009). A Markovian Dependability Model with Cascading Failures. IEEE Transactions On Computers 58, 1238-1249.
  • [6] Malinowski, J. (2017). Modeling hazard-related Interactions between the processes realized in and around the Baltic Sea Region ports. Journal of Polish Safety and Reliability Association, Summer Safety and Reliability Seminars, Vol. 8, No. 1, 87-96.
  • [7] Malinowski, J. (2018). A simple tool for evaluating risks related to hazardous interactions between the processes realized in the Baltic Sea Region’s port areas. Journal of Polish Safety and Reliability Association, Summer Safety and Reliability Seminars, Vol. 9, No. 3, 39-46.
  • [8] Pescaroli, G. & Alexander, D. (2015). A definition of cascading disasters and cascading effects: Going beyond the “toppling dominos” metaphor. In: Planet@Risk 2(3), 58-67, Davos: Global Risk Forum GRF Davos.
  • [9] Swift, A. W. (2008). Stochastic models of cascading failures. Journal of Applied Probability 45, 907-921.
Uwagi
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-0608ad03-606f-4eb0-aada-09b9f4b8bcc7
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.