1926 1. INTRODUCTION AND BACKGROUND Modern surface mines must achieve a delicate balance between productivity and safety in blasting operations. The global transition toward low-carbon technologies has intensified demand for critical minerals, thereby increasing reliance on large-scale open-pit mining. Drill and blast processes are under pressure to consistently produce optimally fragmented (diggable) material while adhering to ever-stricter safety and environmental constraints. In this context, flyrock – rock fragments propelled beyond the designated blast area – remains a high-consequence risk. A flyrock incident can result in injury or loss of life, damage to critical equipment or infrastructure, and operational delays. Despite its significance, flyrock risk management in many mining operations has not advanced at the same pace as other safety improvements due to a lack of understanding (Szendrei & Tose, 2022). Practices tend to be reactive, addressing flyrock only after dangerous incidents occur, and often rely on fragmented tools or rules of thumb that may not account for site-specific conditions. Previous research underscores the complexity of predicting and controlling flyrock (Raina, 2023). Early empirical approaches and safety guidelines provided initial methods to estimate safe stand-off distances. Modern studies have explored varied techniques ranging from statistical regressions and rock engineering system analyses to computational ballistics and machine learning models for flyrock prediction. Notably, recent reviews (Van der Walt & Spiteri, 2020) emphasize the need for more objective, quantitative measurements of flyrock outcomes to improve predictive accuracy. Flyrock hazard management is often disjointed, relying on separate prediction formulas, observational protocols, and incident investigations that are not integrated into a unified process. As a result, flyrock risk may be consistently under or overestimated. For example, at Anglo American’s surface mines, internal safety records historically listed only a handful of flyrock “incidents”. Yet, review of blast videos from the same period revealed that minor flyrock exceedances occur much more frequently than reported, indicating a lack of flyrock awareness and a gap in the analysis process and technology to identify the exceedances. This leads to a false sense of security. To address these issues, a Quantitative Flyrock Risk Management Framework was developed – an integrated approach that links prediction, observation, measurement, and learnings. The framework aims to transform flyrock control from a reactive exercise into a continuous improvement cycle embedded in drill and blast workflows. 2. FRAMEWORK DEVELOPMENT Recognizing the need for a holistic solution, the framework was conceived with the guiding principle of creating a structured risk management process for flyrock. In general, a risk management framework is a structured process that helps operations identify, assess, and reduce risks (International Organization for Standardization, 2023). In developing the framework, key design considerations included: • Risk identification covering the processes and tools used to identify potential risks, including threats, vulnerabilities, and opportunities. • Risk assessment methods to evaluate and prioritize identified risks, considering likelihood, impact, and other factors. • Risk mitigation strategies and controls to reduce or eliminate identified risks, such as avoidance, transfer, or mitigation. • Risk monitoring processes to track and review risks, ensuring that mitigation strategies remain effective.
RkJQdWJsaXNoZXIy MTM0Mzk2