A new study presents the first application of the CRITIC method to weighting geomechanical parameters that affect the stability of underground openings. Using field data from the Ridder-Sokolny mine in Kazakhstan, the authors showed that the method can objectively rank risk-prone design parameters without relying on expert judgement. The results identified internal friction angle and Rock Mass Rating (RMR) as the most influential parameters, highlighting the value of a more data-driven approach to geomechanical risk assessment in underground mining.

Key findings

• The study applies the CRITIC method as an objective weighting strategy for geomechanical risk assessment in underground mining, a context in which it had not previously been used.
• Based on data from the Ridder-Sokolny underground mine, the method ranked internal friction angle first with a weight of 22% and RMR second with 18%, meaning these two parameters together accounted for 40% of the total weight.
• Longitudinal and transverse wave velocities received similar mid-level importance, while cohesion, deformation modulus, and Poisson’s ratio also clustered at comparable weights.
• Uniaxial compressive strength (UCS) received the lowest weight, at about 1%, suggesting that it is less influential than rock-mass-scale parameters in this mine setting.
• When compared with the Entropy method, CRITIC differentiated parameter importance more clearly, while Entropy produced a much more even distribution of weights across parameters.
• The authors note that the method can be implemented without expert input and integrated into practical mine design and risk assessment workflows.

Why it matters
Underground mining design often depends on uncertain geomechanical data, and deciding which parameters matter most is critical for reducing collapse and instability risks. This study offers a replicable, objective, and data-driven way to prioritize key design parameters, which could support safer underground excavation design, more efficient site investigations, and better risk management where expert-based weighting is difficult to obtain. Because the approach does not rely on subjective judgement, it also has potential for broader use in other geotechnical engineering applications.