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• Severity marked failures in an operating system over time are presented as a stochastic risk process. • Risk processes are compared using orders of stochastic dominance. • The components (rate, mean severity, severity exceedance) are dimensions in a probability consequence diagram (PCD). • The PCD is presented as a Risk Cube. • The methods are illustrated with data on operational incidents in an Airport Navigational System. The failure events for a system constitute a marked point process, with severity marks defined by the consequences of failure. In this paper the process is summarized with the triplet: {failure rate, severity mean, severity exceedance}. Those component measures locate the process status in a 3 - dimensional probability consequence diagram. If the dimensions are stratified into intervals, the diagram is displayed as a risk cube. Composite risk measures, which are consistent with orders of stochastic dominance, are defined by integration of the risk process. The composite measures will determine equivalence classes of risk processes, and benchmarks for the measures mark regions of high/low risk on the cube. The risk cube methodology is applied to incident data for an airport navigation system. The location of an individual airport triplet on a risk cube, with regions determined by a family of airports, illustrates the potential for identifying unusual performance in terms of failure events. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to develop safety performance measures and test the measures on data for air traffic management failure events. Failure events are classified by the severity of the consequence of occurrence, resulting in the rate of occurrence in severity categories. The safety measures are standard statistics calculated from this “distribution” for comparison of airport operations by stochastic ordering. For comparisons a benchmark is developed from the aggregation of failure data on a set of comparable airports. Airport performance is then compared with the benchmark using the defined safety measures. The benchmark comparison was implemented with failure data for major airports in Canada from 2005 to 2012. The results show a number of patterns and anomalies and some airports perform poorly in comparison to a class of similar operations. We conclude by suggesting benchmarking safety measures as a natural addition to the information system on aviation safety compiled by a national regulatory body to unravel anomalies such as implementation problems of a safety management system. [ABSTRACT FROM AUTHOR]