RESUMEN
Underground mining is currently one of the Spanish economic sectors with the worst accident rates. Besides, the most frequent type of accident, and with the most serious consequences, is the one in which the injured worker is hit by a moving object. For this reason, this study focuses on the analysis of this type of accident, divided into 3 subgroups to better understand the behavioural patterns. Data mining techniques were applied using the Apriori algorithm to extract as much information as possible about the genesis of these accidents. Similarly, each subset of accidents was processed in two different ways to improve the data analysis, depending on the causal variables used in each case, so that a study of six different scenarios was carried out. The five best association rules or behaviour patterns for each of the six scenarios are shown as a function of their frequency for each rule with 1-4 causal variables.
RESUMEN
BACKGROUND: Mines are hazardous and workers can suffer many types of accidents caused by fire, flood, explosion or collapse. Injury incidence rates in mining are considerably higher than those registered by other economic sectors. One of the main reasons for this high-level incidence rate is the existence of a large number of dangerous workplaces. OBJECTIVE: This work analyzes the influence that occupational safety management had on the accidents that took place in Spanish mining of industrial and ornamental stone during the period 2007-2008. METHODS: Primary data sources are: (a) Results from a statistical study of the occupational health and safety management practices of 71 quarries defined by a questionnaire of 41 items; and (b) Occupational accidents registered in the Spanish industrial and ornamental stone mining throughout the period 2007-2008. RESULTS: The obtained results indicate that workplaces with a low average score in the analysis of occupational safety management have a higher incidence rate of accidents. CONCLUSIONS: Studies on mining workplaces are very important to help detect occupational safety concerns. Results from this study help raise awareness and will encourage the adoption of appropriate measures to improve safety.