Probabilistic downtime estimation for sequential marine operations |
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| Affiliation: | 1. Royal Boskalis Westminster N.V., Papendrecht, the Netherlands;2. Delft University of Technology, Faculty of Civil Engineering and Geosciences, Department of Hydraulic Engineering, Delft, the Netherlands;3. Delft University of Technology, Faculty of Technology, Policy and Management, Safety and Security Science Group, Delft, the Netherlands;1. State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China;2. Collaborative Innovation Center for Advanced Ship and Deep-Sea Exploration, Shanghai Jiao Tong University, Shanghai, 200240, China;3. Department of Naval Architecture and Marine Engineering, University of Strathclyde, Glasgow, G11XQ, United Kingdom;1. Department of Telecommunications and Information Processing, Ghent University - UGent, Sint-Pietersnieuwstraat 41, B-9000 Gent, Belgium;2. Department of Industrial Management, Ghent University - UGent, Technologiepark 903, B-9052 Zwijnaarde, Belgium |
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| Abstract: | A marine project consists of series of operations, with each operation subject to a predefined operational limit and duration. If actual weather conditions exceed the operational limit, the operation cannot be executed and hence downtime occurs. An accurate assessment of uncertainties and the expected downtime during a marine project is important in the tender and execution phase. This paper proposes a new probabilistic model for downtime estimation. It utilizes linked Markov chains that use actual metocean conditions to produce binary workability sequences for each operation. Synthetic time-series can be generated based on the statistics of the past observations and more project simulations are realizable, reducing the simulation uncertainty. The capabilities and limitations of the proposed approach are illustrated in a case study for a hypothetical project in the Tasman Sea. |
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| Keywords: | Simulation Markov theory Marine project operations Offshore Workability Sequences Linked Chains Probability Synthetic Time series Downtime |
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