Professor Forman

7.3 Risk We Face Example – Monitoring the London Underground

For the purpose of illustrating the process of risk assessment and management outlined in Figure 1 – Workflow for Risks-We-Face, we will look at an analysis of the operational risks faced by the intelligent event monitoring system designed by Siemens to monitor degradation of physical assets, such as track signals, and to provide real-time information about train movements along the entire Central Line of London Underground. This analysis was performed by Graduate Students at The George Washington University based on publicly available information[1].  As discussed in Section below, when there are multiple sources, events and objectives the mathematical relationships are non-linear and the results of computations for likelihoods, impacts and risks are inflated and Monte Carlo Simulations are needed to correct for this.  However, in order to understand the relationships between sources, events, objectives, likelihoods, impacts and risks, we will first show computed values ignoring the non-linearities in the following example and then show the simulated results in  the Risks We Face Example with Monte Carlo Simulations, in  Section 7.4 below.

[1] D Wilson. (2014, August 22). London Underground relies on an FPGA-assisted trackmonitoring system to keep the trains rolling safely.

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