The establishment of a coal mining downstream ecosystem focused on a sustainable and environmentally friendly economy is an important goal for many countries. One strategic step in achieving this goal is the utilization of coal fly ash (CFA) waste as a secondary source of rare earth elements (REE). The use of CFA provides a solution to the environmental and health challenges resulting from mining primary sources. Prior to developing REE extraction technology, CFA characterization must be conducted. Therefore, this study addresses the relationship between CFA characteristics and the presence of REE. Based on the ASTM C618-12 standard, CFA in Indonesia is dominated by type F, with Ce being the most abundant REE element. Potential locations for REE sources in Indonesia include power plants in Sumatra, Kalimantan, and the western part of Java. There is a significant correlation between the oxide contents of SiO2, Al2O3, and Fe2O3 with the LREE and CREE groups in CFA in Indonesia. Correlation analysis shows a strong positive relationship between LREE and SiO2 (0.90) and Al2O3 (0.95), while Fe2O3 shows a negative relationship (-0.58). However, Fe2O3 also contributes positively to the presence of CREE (0.89).

The mining industry faces evolving challenges in adapting to the impacts of climate change. Among these challenges is the management of tailings. This study focuses on investigating surface disposal of non-cemented paste tailings, particularly the effect of water content, freeze-thaw cycles (FTC, defined as freezing the sample to –20°C and thawing it to +20°C), and ambient temperature on the mechanical characteristics and thermophysical properties of paste tailings. The potential for maintaining non-cemented tailings in a frozen state year-round is also investigated through field-scale numerical simulations. Experiment results of thermophysical properties of tailings with water content, freeze-thaw cycles and ambient temperatures varying in the 0–30 wt% range, 0–15 range and –5 – –15°C range, respectively, suggest higher thermal conductivity of paste tailings compared with dry porous tailings, particularly at lower temperatures. The highest unconfined compression strength of 0.93 MPa is obtained for the sample with 30 wt% water content, subjected to 15 FTCs at –15°C. This study suggests that, unlike frozen cemented paste tailings, frozen non-cemented paste tailings exhibit higher strength when subjected to more FTCs, making them more resilient in cold regions. Furthermore, the field-scale numerical simulation results support the practicality aspect of frozen paste tailings as a climate change adaptation strategy if combined with artificial ground freezing.

The dynamics of phasing out of hard coal mining are currently the subject of many debates and policies programming the energy transition. Diversity of opinions on the speed of the hard coal mining transition is evident. This discourse uses a number of technical, environmental, economic and social arguments that are not always supported by evidence-based analyses. As assumed in the European Green Deal, a responsible approach to decarbonisation requires just transition values. Thus, the negative effects of mining phasing out should be well recognized to enable their mitigation. This applies especially to the Silesian Voivodeship, where the concentration of so-called coal regions is the highest in the EU. The article formulates scenarios of changes in the labor market in the Silesian Voivodeship and its coal regions, showing the effects of various variants of hard coal mining phase-out up to 2049. The scenarios were constructed based on the “back-casting” methodology and then applied into the portfolio method. The conclusions create a knowledge base enabling a more rational approach to the discussion on the pace of coal mining phase out as key assumptions for strategic documents planning decarbonisation in its various dimensions.

Mine planning involves the systematic design and coordination of mineral extraction from the earth’s crust, integrating exploration, production, and various engineering considerations. With increasing emphasis on environmental responsibility, the mining industry is under pressure to incorporate environmental considerations into mine planning. This paper addresses the precedence-constrained production scheduling problem (PCPSP) within the context of green long-term mining planning, aiming to optimize extraction processes while restricting carbon emission. Given the NP-hard nature of the PCPSP, this study introduces an adaptive large neighborhood search (ALNS) algorithm tailored specifically for long-term mine planning. A range of computational experiments have been carried out, including parameter tuning for the ALNS algorithm, comparisons against an exact solver, and analysis of our destroy-repair operators to determine their key elements. The efficacy of developed ALNS, evaluated using various benchmarks, reveals optimality gaps around 0.08. These results highlight the effectiveness of the proposed approach in addressing the PCPSP within mine planning and production scheduling, providing insights into improving mining operations while considering environmental concerns.

The paper analyses the experience of almost one year of production of “green” electricity by a hydro-generator using a constant water drop in the pits of mine water pumping stations. The main technical, economic and environmental parameters obtained by the applied technical and organisational system are presented. Equipping the mine water pumping station with a hydro-generator proved to be a good investment. The investment offers a relatively low risk with a relatively low initial outlay and a relatively short payback period of about 4 years. The innovative use of typical but modern elements in an atypical operating environment has not been used in Polish mines before. The use of a hydro-generator enables diversification of the energy supply sources of the pumping station, adding the possibility of acquiring renewable energy.

Monitoring drill bit wear during drilling improves operational efficiency. Wear in drill bits is influenced by factors related to drilling parameters and rock properties and can be categorized into types based on the cause of failure. Several studies have used machine learning to detect drill bit wear, mainly using classification models. However, these models require an extensive amount of data that includes different possible drill bit failures. This presents a challenge as acquiring data is difficult due to the scarcity of anomalies. This study introduces a novel approach utilizing convolutional autoencoders (CAE) for both anomaly detection and drill bit damage assessment within rotary percussion drilling. The proposed CAE model was trained on the vibrations of normal data, learning to accurately reconstruct input patterns. A dual threshold was set based on the reconstruction errors of the validation data, serving as a criterion to distinguish between normal and anomalous data. An innovative method for assessing drill bit degradation was developed, utilizing reconstruction errors and thresholds. These findings highlight the significance of adopting advanced machine learning techniques to optimize drilling performance and enhance operational efficiency within the mining field.

The mechanized longwall top-coal caving technology (LTCC) has been used in Quang Ninh underground coal mines owned by Vietnam National Coal – Mineral Industries Holding Corporation Limited (Vinacomin). The application of the LTCC technology has achieved significant achievements, contributing to the production of coal for national economy development. The use of LTCC has shown that the top-coal recovery efficiency is directly affected by the sequence of top coal drawing, ratio of cutting height to caving height, and caving span. These parameters, especially for extracting thick and gently inclined coal seam conditions as in the Quang Ninh coal field, have not been satisfactorily investigated in previous studies, which limits the advantages of this advanced mining technology. By using the numerical software PFC 3.1 as the main analysis tool, this paper studies the relationship between cutting height and caving height for efficient top-coal recovery in extra thick and gently inclined coal seam. Taking the condition of Seam 7, Ha Lam coal mine as a case study, the paper recommends the mine to re-organize its operation with a cutting height-to-caving height ratio of 1:5.25 and caving span of 1.2 m per mining cycle for maximum efficiency of the LTCC operation.

The Stability Graph is a widely used tool for the design of open stopes in underground mining. Many users of the Stability Graph still apply this design method manually. Although the manual approach has benefits, using multiple graphs and stability number computation charts for each stope surface is time-consuming, even for the experienced mining engineer. Current practice in the use of the method also limits data sharing. This paper presents a StopeSoft web-based tool for open stope stability prediction that is developed on the basis of the Stability Graph method and is available at openstope.com. StopeSoft incorporates flexibility in terms of Stability Graph options and incorporates additional critical factors often overlooked. As a web-based tool, StopeSoft encourages and makes data sharing possible globally, focused on expanding the database and improving the current limitations of the Stability Graph to provide practical, reliable solutions for mining engineers, consultants, and academics. The StopeSoft automated process facilitates the process of open stope stability prediction, saving time and minimizing potential human errors. Statistical treatment of the data accounts for the variability of input parameters to emphasize the probabilistic nature of the Stability Graph method. The probabilistic interpretation of the stability states of stope surfaces eliminates the false feeling of absolute stope performance based on its location on the Stability Graph , as implied by the deterministic approach.

Mong Duong mine’s output objective is 1.5 million tons, which requires approximately 10,000 m of tunnel excavation each year. Because of the complicated geological features, the actual work is vastly different, necessitating regular changes in design and technical approaches, as well as plans for material supply, money, and staff. On the other hand, office personnel visit the construction site to update the work status after each report, and the department head and board of directors make choices on development and execution. This process takes time because it is carried out manually. As a result, a solution to support the optimization processes must be identified and implemented. The article gathers data on how each specialized department in the mine develops, classifies information, and builds algorithms to extract outcomes based on the department's responsibilities and functions. The study focuses on the Mong Duong mine. As a result, the director has more information to make timely judgments. The language installer is written in C++ and is free source. This improves job performance, assists employees in retrieving data for work, and reduces manual labor

Significant hazards in Artisanal and small-scale mining (ASM) are rock failure and slope collapse caused by overly steep pit walls, poor mine design and water pressure. There is a lack of expertise and capital in ASM. Providing a simple and cost-effective slope stability analysis and designing systems that can mitigate the risk of slope collapse is essential. This article aims to assess whether stability charts and estimations can be used to establish suitable slope angles to mitigate the overwhelming cases of slope collapse in ASM. The Bieniawski’s Rock Mass Rating system and Heins and Terbrugge stability chart were used to assess the stability of Small-scale mine slope and determine suitable slope angles. To validate the reliability of estimations, further analysis was performed through laboratory strength tests to find actual intact rock mass properties and create a model using OPTUM G2 to simulate the Hoek-Brown failure criterion. The study reveals that stability analysis using charts is applicable with the assistance of a rock engineering practitioner after exposing the intact rock mass to map discontinuities. The Heines and Terbrugge chart can be utilized to mitigate slope collapse in ASM, provided that the limitations of the stability graphs are recognized.