Shuo Yang

Human and Organizational Factors (HOFs) are usually the root causes of complex system failures. Human reliability analysis (HRA) methods to build the structure of HOFs have been proposed. However, they typically lack validated data. To address this limitation, learning from the past has been considered regarding the EU Major Accident Reporting System’s (eMARS) records. Category data analysis has been applied to support the quantitative analysis.

Lacking data has always been a challenging problem for risk analysts on human and organizational factors (HOFs) since the theme comes to birth. Accident reports are an essential source of HOFs information, but they are often in the form of unstructured text, making it challenging to apply the number statistic method directly. The traditional manual coding of accident records could introduce uncertainties and inefficiencies, especially when a large number of records is available.