Evaluating the Normal Accident Theory in Complex Systems as a Predictive Approach to Mining Haulage Operations Safety

Abstract

The Normal Accident Theory (NAT) attempts to understand why accidents occur in systems with high-risk technologies. NAT is characterized by two attributes: complexity and coupling. The combination of these attributes results in unplanned and unintended catastrophic consequences. High-risk technology systems that are complex and tightly coupled have a high probability of experiencing system failures. The mining industry has experienced significant incidents involving haulage operations up to and including severe injuries and fatalities. Although the mining industry has dramatically reduced fatalities and lost time accidents over the last three decades or more, accidents still continue to persist. For example, for the years 1998 - 2002, haulage operations in surface mines alone have accounted for over 40% of all accidents in the mining industry. The systems thinking was applied as an approach to qualitatively and quantitatively evaluate NAT in mining haulage operations. A measurement index was developed to measure this complexity. The results from the index measurements indicated a high degree of complexity that exists in haulage transfer systems than compared to loading and unloading systems. Additionally, several lines of evidence also point to the applicability of NAT in mining systems. They include strong organizational management or safety system does not guarantee zero accidents, complexity is exhibited in mining systems, and they are interactive and tightly coupled systems. Finally, the complexity of these systems were assessed with results indicating that a large number of accidents occur when there are between 4 or 5 causal factors. These factors indicate the degree of complexity necessary before accidents begin to occur.