A model-based approach to system of systems risk management
Andrew Kinder
Michael Henshaw
Carys Siemieniuch
2134/20737
https://repository.lboro.ac.uk/articles/conference_contribution/A_model-based_approach_to_system_of_systems_risk_management/9545099
This 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.
2016-03-30 14:59:25
Systems of systems
Risk
Uncertainty
Risk management modelling
Simulation
Mechanical Engineering not elsewhere classified