Twin Mining provides an AI‑powered Tailings Management System (TMS) that creates a digital twin of tailings facilities, consolidating sensor data, satellite imagery, inspection records, and operational plans into a single platform. The system uses failure‑mode analysis and ALARP‑based risk modeling to predict structural behavior, monitor geochemical and water‑balance parameters, and generate real‑time alerts that help operators maintain compliance with international safety and environmental standards.
Funding
Funding not disclosed
Founders
Product
Problem
Mining operations face significant challenges in safely managing tailings deposits, including fragmented data sources, manual inspection processes, and difficulty meeting international safety and environmental standards. Inadequate integration of monitoring, risk analysis, and operational controls can lead to increased water usage, material loss, and heightened risk of structural failure.
Solution
Twin Mining offers an AI‑powered Tailings Management System (TMS) that unifies operational plans, sensor data, satellite imagery, and inspection records within a single digital twin of the tailings facility. The platform applies failure‑mode analysis (FMEA) and ALARP‑based risk management to anticipate structural behavior and generate proactive alerts. Integrated multi‑source monitoring continuously tracks geochemical evolution, water balance, and environmental trends, enabling predictive water‑use optimization. All data are linked to the physical context of the deposit, providing traceable, real‑time decision support that aligns with international tailings standards throughout the facility lifecycle.
Target Audience
Primary customers are mining companies and tailings facility operators that require comprehensive, standards‑compliant management of tailings deposits, as well as engineering firms providing tailings design and monitoring services.
Features
- Digital twin environment that consolidates plans, roles, sensor streams, satellite data, and field inspections into a unified operational layer
- AI-driven risk modeling using FMEA and ALARP principles to forecast structural failures and suggest mitigation actions
- Continuous multi‑source monitoring of geochemical parameters, water balance, and environmental indicators with automated trend analysis
- Real‑time alert and deviation management workflow that ties findings directly to corrective operational procedures
- Automated documentation of inspections and observations, ensuring traceability to design and operating criteria (KPIs)
- Integration capabilities for chemical stability programs and EMAC compliance reporting