Application of Machine Learning in Mining, Mineral Processing and Extractive Metallurgy
A special issue of Minerals (ISSN 2075-163X). This special issue belongs to the section "Mineral Processing and Extractive Metallurgy".
Deadline for manuscript submissions: 29 August 2025 | Viewed by 776
Special Issue Editors
Interests: mining automation; deep learning; reinforcement learning; applications of machine learning and computer vision in mining
Interests: process engineering; hydrometallurgy; extractive metallurgy; membrane technologies; mine waste valorization
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Machine learning (ML) is one of the most exciting areas in artificial intelligence. Following several decades of the development of different learning techniques, ML is currently being applied in practically all industries. In the fields of mining, mineral processing, and extractive metallurgy, the application of machine learning, and in particular deep learning, has important benefits. Among them, the following stand out: the predictive modeling of processes, which facilitates the prediction of their behavior, the variability of their outputs, and improved control of them; the real-time analysis of material flow to optimize process performance through real-time analysis of operational variables; the predictive maintenance of equipment and components; and the optimization of the use of energy and water. The following Special Issue aims to present innovative applications of ML in mining, mineral processing, and extractive metallurgy, in addition to the quantitative benefits of the applications of ML in real mining plants.
Prof. Dr. Javier Ruiz del Solar
Dr. Humberto Estay
Dr. Pia Lois-Morales
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Minerals is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- machine learning applied to mining, mineral processing, and extractive metallurgy
- predictive modeling of mining and metallurgical processes
- machine learning-based control of mining and metallurgical processes
- machine learning-based water and energy optimization in mining
- machine learning-based optimization of mining and metallurgical processes
- predictive maintenance of equipment and components
- optimization strategies and modeling of metallurgical process performance
Benefits of Publishing in a Special Issue
- Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
- Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
- Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
- External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
- e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.
Further information on MDPI's Special Issue policies can be found here.
