Mining

Despite technological advancements in mining, Chile lacks comprehensive risk management models for tailings storage facilities (TSFs), which hinders the prevention and mitigation of structural and environmental risks. This study aims to develop an integrated risk management model for TSFs in Chile, combining geological and mining engineering with an updated regulatory framework to enhance safety and reduce environmental impacts. The research adopts a mixed-methods approach. Qualitatively, it draws on 10 semi-structured interviews with engineers, geologists, academics, and professionals from the Chilean mining industry, selected through purposive sampling, to explore how and why the current risk management model should be improved. Quantitatively, it analyzes data from 303 surveys assessing the existing regulatory framework, a proposed new regulatory decree for Chile, and key variables to be considered in TSF risk management. The results present a new model that integrates geochemical and geotechnical characterization, process variables, in situ sensors, remote sensing, and artificial intelligence to generate dynamic risk indicators and early warning systems throughout the life cycle of the facility, including closure and liability valuation. Its multiscale design, adaptable to seismic and hydrogeological conditions and suitable for small- and medium-scale mining, overcomes existing static and fragmented approaches, enabling more effective decision-making with a focus on environmental and community safety. The study concludes that the model provides a robust and coherent tool for TSF risk management by integrating technical expertise, the current regulatory framework, and the management of key variables that enhance the ability to anticipate and mitigate structural and environmental risks.

Reliable detection of defects in steel wire ropes is pivotal to ensuring safety and maintaining operational reliability of hoisting and lifting systems in mining and other industries. This study proposes an automated monitoring method based on analyzing the cross-sectional size profile extracted from high-quality visual images. Each image undergoes preprocessing—adaptive binarization, noise suppression, and edge extraction—followed by formation of a one-dimensional thickness profile along the rope’s longitudinal axis. Aggregate statistical descriptors (mean, standard deviation, extrema, and shape descriptors) computed from this profile are supplied to a CatBoost gradient boosting classifier. The model achieves an F1-score exceeding 0.93 across diagnostic categories (intact, bend, kink, break), with particularly high accuracy for critical damage such as wire breaks. Compared with conventional image CNN classifiers, the proposed approach offers higher interpretability, lower computational complexity, and robustness to noise and visual artifacts. The results substantiate the method’s efficacy for real-time automated condition monitoring of mining equipment and its suitability for integration into industrial machine-vision systems. The results substantiate the method’s efficacy for real-time automated condition monitoring of mining equipment and its suitability for integration into industrial machine-vision systems.

Drillstring vibrations are detrimental to drill bits and downhole equipment, affecting drilling efficiency and operational cost in severe drillstring vibration cases. The complex behavior of drillstring vibration, including axial–torsional–lateral coupling and interactions among external forces, necessitated laboratory experiments to address challenges observed in the field. This review paper aims to provide practical insights into essential design considerations that support the effective development of laboratory-scale drillstring experiments. This study analyzes previous work on design methodologies, experimental configurations, measurement techniques, and downhole dynamic simulations. The comparative analysis, highlighting the key similarities and physical design novelties across different experiments, identifies that instrumentation limitations and incoherent downscaling approaches were among the primary setbacks from achieving realistic downscaled experimental models. Fewer studies have examined the interaction between flowing fluids and the drillstring to simulate realistic drilling operations. The study identifies unified experimental configurations across works that simulate similar drilling and vibration dynamics. A comprehensive summary of the foundational knowledge for research-objective-based design suggestions is presented to guide future laboratory-scale drilling vibration experimental design and innovation.