Underground mining is one of the most complex and high-risk work environments, largely due to variable geotechnical conditions and soil behavior uncertainties. Risks of collapse, landslides, and unexpected ground movements pose a constant danger to workers and directly affect project feasibility and costs. Traditionally, engineers have relied on laboratory tests and on-site analyses to assess ground stability; however, these methods come with significant uncertainties. Artificial Intelligence (AI) and real-time analytics are revolutionizing risk management in underground mining by providing predictive tools and data-driven decision-making capabilities, essential for optimizing both operational safety and efficiency.
The Importance of AI in Underground Mining
AI in underground mining allows for the analysis of large volumes of real-time data, integrating information from various sources such as topography, inclinometers, sliding micrometers, and piezometers. This continuous analysis capability enables the monitoring and prediction of ground behavior, identifying issues before they become critical threats to safety or cause costly operational stoppages. By combining historical and current data, AI provides a more precise understanding of the terrain, allowing for immediate adjustments and reducing accident risks.
How Real-Time Analysis and AI Reduce Geotechnical Uncertainty
Uncertainty in ground behavior is a persistent challenge in underground mining projects. Generally, the industry has addressed these uncertainties by applying conservative safety factors in structural designs. While this practice minimizes some risks, it also results in higher costs due to structural over-dimensioning. This is where real-time data analysis, enabled by AI, offers a solution: by comparing live monitoring data with numerical or "digital twin" models of the terrain, AI can significantly reduce these uncertainties, allowing for a more precise design that optimizes both safety and resources.
DAARWIN: Transforming Risk Management in Underground Mining
DAARWIN, the cloud-based platform from SAALG Geomechanics, is an innovative example of how AI technology is being used to connect and analyze geotechnical data in real time. This platform allows geotechnical engineers to manage borehole and soil test data in an automated way, integrating results from Cone Penetration Tests (CPT), laboratory analyses, and in-situ tests into detailed geological models. Supported by OCR technology, DAARWIN rapidly digitizes diverse borehole information formats, minimizing human error and allowing engineers to focus more on data interpretation and analysis.
Through real-time analysis, DAARWIN provides a detailed visualization of ground models and geological profiles, helping engineers identify potential risks and plan proactively. This capability to create accurate models and automatically transfer digitized parameters to numerical models enables engineers to conduct more accurate risk assessments, which not only enhances safety but also optimizes project timelines and reduces costs.
The use of DAARWIN in underground mining facilitates informed decision-making based on comprehensive real-time data analysis, resulting in substantial improvements in safety, efficiency, and sustainability. By minimizing uncertainty and optimizing risk management, DAARWIN helps reduce costs and improve project timelines. The AI technology integrated into this platform provides mining companies with the capability to manage their projects more sustainably, reducing the need for redundant testing and analyses while generating more reliable and high-quality engineering solutions.
