Abstract
Slope stability is a critical factor in ensuring mining operations' safety, efficiency, and sustainability. Characterizing rock slope stability and identifying and prioritizing its influencing factors is fundamental to achieving sustainable mining operations, proactive risk management, and mining resource optimization. This study aims to systematically evaluate and prioritize the factors influencing slope stability in mines using a Pareto-Optimized Hierarchical Structural Interaction Matrix (P-HSIM), whose prioritization computation is based on the theory of subordination derived through systems thinking. To achieve this aim, the various factors influencing slope stability were identified and collated from the literature. A Binary Interaction Matrix (BIM) that assesses the relative importance and interdependencies among geotechnical, geological, environmental, and other factors was developed. The outcome of the BIM simulation was evaluated numerically using relevant mathematical equations to calculate the intensity rating score of every slope stability influencing factor. A Pareto optimization technique was then applied to enhance the prioritization process to ensure that the most significant slope stability influencing factors are appropriately emphasized. The study highlights the versatility of the P-HSIM framework in addressing complex geotechnical challenges and its potential to support sustainable mining practices by reducing geohazards, minimizing environmental impact, and enhancing resource efficiency. The findings offer a novel decision-making tool for mining engineers and sustainability practitioners, contributing to developing safer and more environmentally conscious mining operations.