Forthcoming and Online First Articles

International Journal of Mining and Mineral Engineering

International Journal of Mining and Mineral Engineering (IJMME)

Forthcoming articles have been peer-reviewed and accepted for publication but are pending final changes, are not yet published and may not appear here in their final order of publication until they are assigned to issues. Therefore, the content conforms to our standards but the presentation (e.g. typesetting and proof-reading) is not necessarily up to the Inderscience standard. Additionally, titles, authors, abstracts and keywords may change before publication. Articles will not be published until the final proofs are validated by their authors.

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International Journal of Mining and Mineral Engineering (3 papers in press)

Regular Issues

  • Hybrid Machine Learning Techniques to Predict Fuel Consumption of Dump Trucks in an Open-Pit Mine in Peru   Order a copy of this article
    by Marco Antonio Cotrina Teatino, Jairo Jhonatan Marquina Araujo, Jose Nestor Mamani Quispe, Solio Marino Arango Retamozo, Joe Alexis Gonzalez Vasquez, Eduardo Manuel Noriega Vidal, Eusebio Antonio Araujo 
    Abstract: Mining dump trucks account for 31% of energy consumption and up to 60% of operating costs in open pit mines. This study aims to predict the fuel consumption of mining dumpers in an open pit mine in Peru by applying innovative hybrid machine learning models, including artificial neural networks (ANN), decision trees (DT) and random forests (RF), optimised with genetic algorithms (GA). The models evaluated the efficiency and cost savings of replacing 24 m3 dump trucks with 26 m3 dump trucks. The data were divided into 70% for training and 30% for testing. Input variables included utilisation, operating hours and total trips. The RF + GA model achieved the highest accuracy (R2 = 0.89, RMSE = 250.05, MAE = 185.09), followed by ANN + GA with an R2 of 0.87 and DT + GA with R2 of 0.86. This novel approach significantly improves the prediction accuracy, showing that replacing dump trucks can save an average of US$1.76 per hour.
    Keywords: mining dump trucks; fuel consumption; hybrid techniques; machine learning; genetic algorithms.
    DOI: 10.1504/IJMME.2025.10066537
     
  • Optimise a Ventilation System in Underground Mines using Artificial Neural Networks   Order a copy of this article
    by Marco Antonio Cotrina Teatino, Jose Nestor Mamani Quispe, Solio Marino Arango Retamozo, Jairo Jhonatan Marquina Araujo, Eduardo Manuel Noriega Vidal, Dominga Cano Ccoa, Teofilo Donaires Flores, Joe Alexis Gonzalez Vasquez, Tomas Anticona Cueva 
    Abstract: This study aimed to optimise ventilation systems in underground mines using artificial neural networks (ANNs) to reduce temperature and relative humidity while improving airflow. A dataset of 66 samples was used to train the ANN model, which included 4 input parameters, 128 and 64 hidden neurons, and 3 output parameters. The model was tested with 70% of data in training and 30% in validation. The results demonstrated that the ANN showed strong predictive performance for temperature and humidity, achieving R2 values of 0.88 and 0.96, respectively, in the validation data. Additionally, the model achieved an R2 of 0.81 for airflow data, indicating reliable predictions. The ANN also successfully optimised the ventilation parameters, resulting in a temperature reduction of 6.13
    Keywords: Ventilation; underground mines; artificial neural networks.
    DOI: 10.1504/IJMME.2025.10068388
     
  • Methods, Developments and Inspections in Mine Shaft Sinking - a Review   Order a copy of this article
    by Wojciech Rutkowski 
    Abstract: This review article examines various methods for shaft sinking, presenting a range of possibilities for developing vertical mine openings. It describes different mechanical rock-breaking methods as well as drill and blast techniques. Additionally, it covers aspects of innovative shaft sinking technologies in the Polish Copper industry. Drawing from KGHM Polish Coppers experience, the article discusses types of mine shaft linings, including tubing lining with the freezing method, concrete or reinforced concrete lining, and final equipment such as rail and line guides. The review also addresses maintenance issues related to shaft sinking methods, mentioning challenges like the rheological properties of rock salt in the SW-4 mine shaft. Given the critical importance of safety in the mining industry, a significant portion of this review emphasises inspections and measurements in mine shafts. The article also describes both innovative and established solutions that enhance safety in mining, such as laser scanning and photogrammetry in mine shafts, as well as unmanned vehicles in underground mining operations.
    Keywords: mineshaft sinking; underground mining; safety inspections; measurement.
    DOI: 10.1504/IJMME.2025.10068564
     

 

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