Foresight in process industry through dynamic risk assessment: implications and open questions
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Risk analysis is about to enter an era of larger and more complex data sets (big data), where the main challenges are represented by the ability to provide continuous acquisition, effective process and meaningful communication of information. However, most of the methods for quantitative risk assessment allow for static evaluations of risk in a frozen instant of the system life. Research on how to dynamically assess risk in process industry has been carried out, but no real implementation has been attempted. Some open questions are still undermining this approach and should be directly addressed to provide reliable models and exploit new technology opportunities. i) Which strategy should be adopted? ii) How early warnings and past events should be assessed and connected to the overall risk? This contribution aims to give an overview on preliminary answers and highlight possible uncertainties of future developments.