Evidence in the literature shows that human actions are a source of vulnerability for industrial systems, giving rise to HRA that aims to deepen the examination of the human factor in the workplace1. HRA is concerned with identifying, modelling, and quantifying the probability of human errors2Nominal human error probability (HEP) is calculated on the basis of operator’s activities and, to obtain a quantitative estimate of HEP, many HRA methods utilise performance shaping factors (PSF), which characterise significant facets of human error and provide a numerical basis for modifying nominal HEP levels3. The PSF are environmental factors, personal, or directed to activities that have the potential to affect performance positively or negatively; therefore, identifying and quantifying the effects of a PSF are key steps in the process of HRA4 Another key step concerns interpretation and simulation of human behaviour, which is a dynamic process driven by cognitive and behavioural rules, and influenced by physical and psychological factors. Human behaviour, although analysed in numerous studies, remains difficult to fully represent in describing all the nuances that distinguish it5. It is abundantly clear how complex an effort has been made in the literature to propose models of human behaviour, favoring numerical values of probability of error to predict and prevent unsafe behaviours. For this reason, the study of human reliability can be seen as a specialised scientific subfield – a hybrid between psychology, ergonomics, engineering, reliability analysis, and system analysis6.
The birth of HRA methods dates from the year 1960, but most techniques for assessment of the human factor, in terms of propensity to fail, have been developed since the mid-’80s. HRA techniques or approaches can be divided essentially into two categories: first and second generation. Currently, we come to HRA dynamic and methods of the third generation, understood as an evolution of previous generations.
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