Assessment of expected production of a deep-sea mining system

An integrated model-based systems engineering and discrete event simulation approach

Journal article (2023)

Authors

Astrid V. Solheim Norwegian University of Science and Technology (NTNU)
Antoine B. Rauzy Norwegian University of Science and Technology (NTNU)
Per Olaf Brett Ulstein International A.S., Norwegian University of Science and Technology (NTNU)
Steinar Ellefmo Norwegian University of Science and Technology (NTNU)
Tonje Hatling Norwegian University of Science and Technology (NTNU)
R.L.J. Helmons Offshore and Dredging Engineering - Mechanical, Maritime and Materials Engineering , Norwegian University of Science and Technology (NTNU)
Bjørn Egil Asbjørnslett Norwegian University of Science and Technology (NTNU)
Research Group
Offshore and Dredging Engineering (Mechanical, Maritime and Materials Engineering) (TU Delft)
Copyright: © 2023 Astrid V. Solheim, Antoine B. Rauzy, Per Olaf Brett, Steinar Ellefmo, Tonje Hatling, R.L.J. Helmons, Bjørn Egil Asbjørnslett
DOI: https://doi.org/10.1002/sys.21699
More Info
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Published Date

2023

Language

English

Faculty

Mechanical, Maritime and Materials Engineering

Department

Marine and Transport Technology

Research Group

Offshore and Dredging Engineering

Abstract

In this paper, model-based systems engineering (MBSE) and discrete event simulation (DES) are combined to assess the performance of an offshore production system at an early stage. Various systems engineering tools are applied to an industrial case concerning the retrieval of deep-sea minerals, and a simulation engine is developed to calculate the annual production output. A mean production of 1 Million tonnes of ore per year is estimated for an operation in the Norwegian Sea using Monte Carlo simulation. Depending on the limiting design wave height of the marine operations, the estimated production output ranges from 280,000 tonnes to 1.8 Million tonnes per year. The constrained parameter of the production system is particularly the wave height operational limit of the ship-to-ship transfer operation. We present the learning outcome from applying MBSE and DES to this case and discuss important aspects for improved performance.