A Clustering Approach to a Major-Accident Data Set: Analysis of Key Interactions to Minimise Human Errors

This work aims to scrutinise a proprietary dataset containing major accidents occurred in high-technology facilities, in order to disclose relevant features and indicate a path to the recognition of the genesis of human errors. The application of a tailored Hierarchical Agglomerative Clustering method will provide means to understand data and identify key similarities among accidents and significant interfaces between human factors, the organisational environment and the technology. Conclusions to improve the human performance based on the clustering results are then discussed.