Content area
The recent tailings storage facility (TSF) dam failures recorded around the world have concerned society in general, forcing the mining industry to improve its operating standards, invest greater economic resources, and implement the best available technologies (BATs) to control TSFs for safety purposes and avoid spills, accidents, and collapses. In this context, and as the era of digitalization and Industry 4.0 continues, monitoring technologies based on sensors have become increasingly common in the mining industry. This article studies the state of the art of implementing sensor technologies to monitor structural health and safety management issues in TSFs, highlighting advances and experiences through a review of the scientific literature on the topic. The methodology applied in this article adheres to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and utilizes scientific maps for data visualization. To do so, three steps were implemented: (i) a quantitative bibliometric analysis, (ii) a qualitative systematic review of the literature, and (iii) a mixed review to integrate the findings from (i) and (ii). As a result, this article presents the main advances, gaps, and future trends regarding the main characteristics of the sensor technologies applied to monitor TSF structural health and safety management in the era of digitalization. According to the results, the existing research predominantly investigates certain TSF sensor technologies, such as wireless real-time monitoring, remote sensors (RS), unmanned aerial vehicles (UAVs), unmanned survey vessels (USVs), artificial intelligence (AI), cloud computing (CC), and Internet of Things (IoT) approaches, among others. These technologies stand out for their potential to improve the safety management monitoring of mine tailings, which is particularly significant in the context of climate change-related hazards, and to reduce the risk of TSF failures. They are recognized as emerging smart mining solutions with reliable, simple, scalable, secure, and competitive characteristics.
Details
Scientific visualization;
Remote sensors;
Internet of Things;
Sensors;
Context;
Signal processing;
Industry 4.0;
Unmanned aerial vehicles;
Mining;
Energy transition;
Mine tailings;
Monitoring systems;
Failures;
Structural health monitoring;
Social responsibility;
Qualitative analysis;
Construction;
Tailings;
Economic resources;
Artificial intelligence;
Industrial applications;
Safety;
Dam failure;
Risk reduction;
Mining industry;
Climate change;
Failure;
Data processing;
Remote monitoring;
Literature reviews;
Survey vessels;
Safety management;
Sustainable development;
Cloud computing;
State-of-the-art reviews;
Digitization;
Distributed control systems;
Mine wastes;
Storage facilities;
Mining accidents & safety;
Human error;
Digital technology
1 Department of Civil Works and Geology, Catholic University of Temuco, Temuco 4780000, Chile;
2 Department of Civil Works and Geology, Catholic University of Temuco, Temuco 4780000, Chile;
3 Department of Civil Engineering, Universidad de Castilla-La Mancha, Av. Camilo Jose Cela s/n, 13071 Ciudad Real, Spain;