Tailings waste backfill treatment has become a crucial approach for sustainable mining and green mine construction. Conventional backfill involves problems such as unstable operation, reliance on manual equipment, low efficiency, and major safety hazards. Recent advances in intelligence have provided opportunities to advance backfill operations. This paper introduces an intelligent backfill operation and control system. It integrates sensing, decision-making, and execution to achieve efficient, safe, and adaptive backfill management. The system adopts a layered architecture. Onsite sensors collect real-time data. These are subsequently processed by a programmable logic controller (PLC) and integrated into a system. Intelligent operation and control strategies were implemented across three key stages of the backfill process: tailing thickening, slurry mixing and preparation, and pipeline transportation. During the thickening of tailings, mathematical models were established to regulate the solid mass fraction (SMF) of the tailing-feeding slurry and the flow rate of the flocculant dosage. This ensured an optimal SMF in the deep drone thickener and safe control of the rake torque. During slurry mixing and preparation, the backfill control system automatically adjusts the amount of cementitious material added, flow rate of dilution water, and pinch valve operation based on real-time monitoring. This improves the slurry quality and stability. For pipeline transportation, real-time pressure monitoring can rapidly detect obstructions, ruptures, and incompletely filled conditions, and automatically initiate corrective actions to prevent system failures. Additionally, the backfill control system adopts an intelligent water circulation strategy to conduct closed-loop monitoring and distribution of process water. This significantly improves the circulation efficiency and reduces the overall resource consumption.
Liu et al. (2026) studied this question.