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A model-based approach to system of systems risk management
conference contribution
posted on 2016-03-30, 14:59 authored by Andrew Kinder, Michael HenshawMichael Henshaw, Carys SiemieniuchThis paper discusses the approaches required for risk management of ‘traditional’ (single) Systems and System of Systems (SoS) and identifies key differences between them. When engineering systems, the Risk Management methods applied tend to use qualitative techniques, which provide subjective probabilities and it is argued that, due to the inherent complexity of SoS, more quantitative methods must be adopted. The management of SoS risk must be holistic and should not assume that if risks are managed at the system level then SoS risk will be managed implicitly. A model-based approach is outlined, utilizing a central Bayesian Belief Network (BBN) to represent risks and contributing factors. Supporting
models are run using a Monte Carlo approach, thereby generating results, which may be ‘learnt’ by the BBN, reducing the reliance on subjective data.
History
School
- Mechanical, Electrical and Manufacturing Engineering
Published in
2015 10th System of Systems Engineering Conference (SoSE) System of Systems Engineering Conference (SoSE), 2015 10thPages
122 - 127 (6)Citation
KINDER, A., HENSHAW, M. and SIMIENIUCH, C.E., 2015. A model-based approach to system of systems risk management. IN: Proceedings of 2015 10th IEEE System of Systems Engineering Conference (SoSE), San Antonio, United States, 17-20 May 2015, pp.122-127.Publisher
© IEEEVersion
- VoR (Version of Record)
Publisher statement
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2015Notes
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Language
- en