Citation

Alexander R, Kelly T. Safety Sci. 2013; 51(1): 302-318.

Copyright

(Copyright © 2013, Elsevier Publishing)

DOI

10.1016/j.ssci.2012.07.006

PMID

unavailable

Abstract

When engineers create a safety-critical system, they need to perform an adequate hazard analysis. For Systems of Systems (SoSs), however, hazard analysis is difficult because of the complexity of SoS and the environments they inhabit. Traditional hazard analysis techniques often rely upon static models of component interaction and have difficulties exploring the effects of multiple coincident failures. They cannot be relied on, therefore, to provide adequate hazard analysis of SoS. This paper presents a hazard analysis technique (SimHAZAN) that uses multi-agent modelling and simulation to explore the effects of deviant node behaviour within a SoS. It defines a systematic process for developing multi-agent models of SoS, starting from existing models in the MODAF architecture framework and proceeding to implemented simulation models. It then describes a process for running these simulations in an exploratory way, bounded by estimated probability. This process generates extensive logs of simulated events; in order to extract the causes of accidents from these logs, this paper presents a tool-supported analysis technique that uses machine learning and agent behaviour tracing. The approach is evaluated by comparison to some explicit requirements for SoS hazard analysis, and by applying it to a case study. Based on the case study, it appears that SimHAZAN has the potential to reveal hazards that are difficult to discover when using traditional techniques.