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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 Siemieniuch
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.

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Published in

2015 10th System of Systems Engineering Conference (SoSE) System of Systems Engineering Conference (SoSE), 2015 10th

Pages

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

© IEEE

Version

  • VoR (Version of Record)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Publication date

2015

Notes

THIS DOCUMENT IS CLOSED ACCESS. © 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Language

  • en

Location

San Antonio

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