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A computational tool for general model of industrial systems operations processes

Treść / Zawartość
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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The complexities of real industrial systems operation processes require computational methods that can analyze the large data and evaluate the behaviours of these systems. The use of methods such as Bayesian Network, Formal Safety Assessment and Statistical-Model based method were discussed as possibilities. Of which, a computational tool, based on the Semi-Markov model, was developed. This tool was then applied to analyze the behaviour of the operation processes of the oil transportation system in Dębogórze, Poland. The analyses showed that the computational solutions generated compared favorably well with the analytical calculations, enabling possible extensions of the tool to include reliability and optimization evaluations to be explored.
Rocznik
Tom
Strony
295--302
Opis fizyczny
Bibliogr. 19 poz., rys., tab.
Twórcy
autor
  • Institute of High Performance Computing, Singapore
  • Institute of High Performance Computing, Singapore
  • Gdynia Maritime University, Poland
  • Gdynia Maritime University, Poland
autor
  • National University of Singapore
Bibliografia
  • [1] Blokus-Roszkowska, A., Kołowrocki, K. (2008). Modelling environment and infrastructure of shipyard transportation systems and processes. Proc. 2nd Summer Safety and Reliability Seminars (SSARS), Vol. 1, 77-84.
  • [2] Eleye-Datubo, A. G., Wall, A. & Wang, J. (2008). Marine and Offshore Safety Assessment by Incorporative Risk Modeling in a Fuzzy-Bayesian Network of an Induced Mass Assignment Paradigm. Risk Analysis, Vol 28, 95-112.
  • [3] Felli, J. C., Anderson, W. H., Kremida, J. P. & Ruberg, S. J. (2007). A semi-Markov model for patient progression through clinical trials. European Journal of Operation Research 176, 542-549.
  • [4] Grabski, F. (2002). Semi-Markov Models of Systems Reliability and Operations. Warsaw: Systems Research Institute, Polish Academy of Sciences.
  • [5] Guze, S., Kołowrocki, K. & Soszyńska, J. (2008). Modelling environment and infrastructure influence on reliability and operation processes of port oil transportation system. Proc. 2nd Summer Safety and Reliability Seminars (SSARS), Vol. 1, 179-186.
  • [6] Heyman, D. P. & Sobel, M. J. (2003). Stochastic models in operations research, Vol I: Stochastic processes and operating characteristics. Dover Publications.
  • [7] Hu, S., Fang, Q., Xia, H. & Xi, Y. (2007). Formal safety assessment based on relative risks model in ship navigation. Reliability Engineering & System Safety, Vol 92, 369-377.
  • [8] International Maritime Organization (IMO) (2002). Guidelines for Formal Safety Assessment (FSA), IMO MSC/Circ 1023.
  • [9] Jin, D. & Thunberg, E. (2005). An analysis of fishing vessel accidents in fishing areas off the northeastern United States. Safety Science, Vol 43, 523-540.
  • [10] Kołowrocki, K. & Soszyńska, J. (2008). A general model of industrial systems operations processes related to their environment and infrastructure. Proc. 2nd Summer Safety and Reliability Seminars (SSARS), Vol. 2, 223-226.
  • [11] Lee, J., Yeo, I. & Yang, Y. (2001). A trial application of FSA methodology to the hatchway watertight integrity of bulk carriers. Marine Structures, Vol 14, 651-667.
  • [12] Norrington, L., Quigley, J., Russell, A. & Van der Meer, R. (2008). Modelling the reliability of search and rescue operations with Bayesian Belief Network. Reliability Engineering & System Safety, Vol 93, 940-949.
  • [13] Pearl, J. (1985). Bayesian networks: A model of self-activated memory for evidential reasoning. Proc. 7th Conference of the Cognitive Science Society, 329-334.
  • [14] Perman, M., Senegacnik, A. & Tuma, M. (1997). Semi-Markov Models with an application to Power-Plant Reliability Analysis. IEEE Transactions on Reliability, Vol 46, No 4.
  • [15] Ruud, S. & Age, M. (2008). Risk-based rules for crane safety systems. Reliability Engineering & System Safety, Vol 93, 1369-1376.
  • [16] Trucco, P., Cagno, E., Ruggeri, F. & Grande, O. (2008). A bayesian belief network modeling of organizational factors in risk analysis: A case study in maritime transportation. Reliability Engineering & System Safety, Vol 93, 845-856.
  • [17] Vinod, G., Bidhar, S. K., Kushwaha, H. S., Verma, A. K. & Srividya, A. (2003). A comprehensive framework for evaluation of piping reliability due to erosion-corrosion for risk-informed in service inspection. Reliability Engineering and System Safety, Vol 82, 187-193.
  • [18] Wang, J. (2002). Offshore safety case approach and formal safety assessment of ships,. Journal of Safety Research, Vol 33, 81-115.
  • [19] Wang, J., Pillay, A., Kwon, Y. S., Wall, A. D. & Loughran, C.G. (2005). An analysis of fishing vessel accidents. Accident Analysis & Prevention, Vol 37, 1019-1024.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-81cabff0-385b-4269-ac42-56f1f444000e
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