JH
J. Hanselaar
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Model-Based Systems Engineering with Integrated Decision-Support for Early-Stage Offshore Vessel Design
Configuring and Evaluating Vessel Systems Architectures in Capella Using a Cooling Water System Case Study
The increasing complexity of offshore vessels requires improved methods to evaluate system architectures during early-stage design. Current design approaches often assess subsystems separately, limiting the ability to explore system-level trade-offs between cost, reliability, and operational performance. This paper presents an MBSE-based decision support framework for the automated generation and evaluation of offshore vessel system architectures. The proposed approach integrates a Capella-based system model with automated architecture extraction, configuration generation, and multi-criteria evaluation. Alternative architectures are assessed by combining cost modelling with reliability-based risk analysis. The framework is demonstrated through an offshore vessel cooling system case study, where multiple configurations are generated and compared. The results show that the framework can identify cost-risk trade-offs between different levels of redundancy and system integration, supporting the selection of balanced architectures. The proposed methodology extends the application of MBSE from system modelling towards quantitative architecture exploration, providing designers with a structured approach for more informed decision-making during concept design.
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The increasing complexity of offshore vessels requires improved methods to evaluate system architectures during early-stage design. Current design approaches often assess subsystems separately, limiting the ability to explore system-level trade-offs between cost, reliability, and operational performance. This paper presents an MBSE-based decision support framework for the automated generation and evaluation of offshore vessel system architectures. The proposed approach integrates a Capella-based system model with automated architecture extraction, configuration generation, and multi-criteria evaluation. Alternative architectures are assessed by combining cost modelling with reliability-based risk analysis. The framework is demonstrated through an offshore vessel cooling system case study, where multiple configurations are generated and compared. The results show that the framework can identify cost-risk trade-offs between different levels of redundancy and system integration, supporting the selection of balanced architectures. The proposed methodology extends the application of MBSE from system modelling towards quantitative architecture exploration, providing designers with a structured approach for more informed decision-making during concept design.