Evaluation of safety performance remains central to any safety and risk management. Currently, there are very few support tools and methods which allow for quantitative approach in this domain. One of the successful methods available to this end is the Aerospace Performance Factor (APF). The method is based on hierarchical clustering of taxonomy-based safety performance indicators, using simple and intelligible formula to compute the overall safety performance signal. The work presented in this study deals with one of the APF shortcomings, namely the absence of nonlinear relations among the performance indicators to capture more accurately the risk in the assessed system. It proposes an addition of new decision criteria behind the APF method as part of the application of Analytical Hierarchy Process (AHP), namely the impact of respective performance indicator on other indicators, regardless of their hierarchical structure. This addition leads to relative changes of performance indicators significance, where those with the highest potential for nonlinear interactions among the entire set of performance indicators are emphasized and the change in their weight ultimately leads to changes in the overall APF signal. The study results indicate that the extended APF signal is refined in terms of extremes and it draws more accurate picture about the actual safety performance, eventually supporting better identification of deviations from its acceptable values. The study was experimentally carried out in the aviation with data from the European Central Repository (ECR) originating from United Kingdom during the years 2013-2015 and verified further on data sets from Finland and Denmark.

Faculty of Transportation Sciences Czech Technical University Prague Czech Republic

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