Mine Management Optimization in the Era of AI and Advanced Analytics
A special issue of Mining (ISSN 2673-6489).
Deadline for manuscript submissions: 20 December 2025 | Viewed by 39
Special Issue Editors
Interests: systems integration; data analytics; health and safety; machine learning; internet of things
Special Issues, Collections and Topics in MDPI journals
Interests: data analytics; mine management; artificial intelligence; operation research; business intelligence; simulation
Interests: tailings dewatering; tailings material characterization; tailings backfill; management of tailings storage facilities
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The mining industry is undergoing a profound transformation driven by artificial intelligence (AI) and advanced analytics. This Special Issue explores how these technologies are reshaping mine management across the entire value chain, ranging from geological exploration and resource estimation to mine planning, operations, mineral processing, and mine waste management. With the rapid growth of digitalization, mining companies must adopt data-driven decision-making, real-time optimization, and predictive analytics to enhance efficiency, sustainability, and safety.
This Special Issue invites research on novel AI-driven approaches, including machine learning for predictive maintenance, short-interval control for real-time decision-making, autonomous systems integration, and digital twins for mine process optimization. Case studies on successful implementations and experimental applications will be particularly valuable, providing insights into overcoming barriers to adoption. The focus is on practical, scalable, and innovative solutions that drive operational excellence, reduce costs, and improve sustainability. Given the need for rapid adoption, contributions highlighting agile deployment, iterative experimentation, and lessons learned in AI-driven mine management will be prioritized.
Dr. Pratt Rogers
Dr. Muhammet Mustafa Kahraman
Dr. Yuan Li
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. Mining is an international peer-reviewed open access quarterly 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 1000 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
- mine optimization
- short interval control
- AI-driven decision making
- autonomous mining systems
- digital twins in mining
- predictive analytics for mine operations
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