Structural Equations Model for accident analysis based on the Human Factors Classification System in underground mines in Peru

Romero-Ramos F.; Trujillo-Torres J.; Aramburú-Rojas V.; Raymundo C. · Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology (2021) · DOI: 10.18687/laccei2021.1.1.504

Resumen

Mining is an industry where workers interact in the different stages of mining exploitation in the face of innumerable risks that threaten their integrity. For this reason, investigations have been developed that have sought to solve this problem from different approaches. The contribution of this research is to generate an accident analysis model studying human factors with the application of the Human Factors Analysis and Classification System (HFACS) and the Structural Equations Model of minimal partial frames (PLS-SEM) to a qualitative and quantitative analysis. When applying this model to the analysis of accidents that occurred in underground mining in Peru, it was evidenced that organizational influences have a significant effect on external factors, this in turn has an effect on the preconditions for unsafe acts. Furthermore, unsafe leadership and the preconditions for unsafe acts have a significant and positive relationship on unsafe acts. In summary, it has been proven that the proposed hybrid model is appropriate for analyzing accidents in underground mines.

Instituciones: Universidad Peruana de Ciencias Aplicadas