Applied Chemical Engineering

Machine learning applications in ore grade estimation and blending optimization for modern mining

Dipa Dattatray Dharmadhikari

Emerging Science and Technology Department, Maharashtra Institute of Technology, Chatrapati Sambhajinagar, Aurangabad - 431010, Maharashtra, India.

Avani Ray

Department of Computer Engineering, PCET’s Pimpri Chinchwad College of Engineering and Research, Ravet, Pune - 412101, Maharashtra, India.

Babaso A. Shinde

Department of Artificial Intelligence and Data Science, Marathwada Mitramandal’s Institute of Technology, Lohgaon, Pune - 411047, Affiliated to Savitribai Phule Pune University, Maharashtra, India.

Sandeep V. Raut

Department of Mechanical Engineering, ABMSP’s Anantrao Pawar College of Engineering and Research, Parvati, Pune - 411009, Maharashtra, India.

Rupali Dineshwar Taware

MCA Department (Commerce and Management), Vishwakarma University, Laxminagar, Kondhwa (Bk.), Pune – 411048, Maharashtra, India.

Smita Desai

Department of Electronics and Telecommunication, Dr. D. Y. Patil Institute of Technology, Sant Tukaram Nagar, Pimpri, Pune, 411018, Maharashtra, India; Dnyaan Prasad Global University (DPGU), School of Technology and Research - Dr. D. Y. Patil Unitech Society, Sant Tukaram Nagar, Pimpri, Pune, 411018, Maharashtra, India

Shital Yashwant Waware

Department of Mechanical Engineering, Dr. D. Y. Patil Institute of Technology, Sant Tukaram Nagar, Pimpri, Pune, 411018, Maharashtra, India ; Dnyaan Prasad Global University (DPGU), School of Technology and Research - Dr. D. Y. Patil Unitech Society, Sant Tukaram Nagar, Pimpri, Pune, 411018, Maharashtra, India

Anant Sidhappa Kurhade

Department of Mechanical Engineering, Dr. D. Y. Patil Institute of Technology, Sant Tukaram Nagar, Pimpri, Pune, 411018, Maharashtra, India ; Dnyaan Prasad Global University (DPGU), School of Technology and Research - Dr. D. Y. Patil Unitech Society, Sant Tukaram Nagar, Pimpri, Pune, 411018, Maharashtra, India

DOI: https://doi.org/10.59429/ace.v8i4.5790

Keywords: Artificial neural networks; blending optimization; grade estimation; mining 4.0; machine learning; predictive modeling

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Abstract

The growing complexity of mineral deposits and the demand for sustainable, cost-effective mining have driven the adoption of machine learning (ML) for ore grade estimation and blending optimization. This review critically examines how ML models—such as ANN, SVM, RF, and ensemble techniques—surpass traditional geostatistical methods in handling non-linear spatial variability and limited sampling. The paper emphasizes hybrid frameworks that combine ML with geostatistics, optimization algorithms (GA, PSO, RL), and digital technologies like IoT and digital twins for real-time, adaptive decision-making. Key findings indicate that ML-based systems significantly enhance prediction accuracy, blending precision and operational efficiency while reducing waste and energy consumption. Despite these advancements, issues related to data quality, model interpretability, interoperability, and ethics remain. The study outlines future directions emphasizing explainable AI, standardized benchmarking, and robust data infrastructures for transparent and sustainable implementation of ML in mining. Recent industrial deployments illustrate the practical impact of ML in mining operations. For instance, Australian and Canadian mines have integrated ML-based ore grade control and real-time blending optimization systems, resulting in 10–15% improvements in recovery rates and reduced energy consumption. Similarly, predictive maintenance and digital twin frameworks powered by ML are being used by global firms such as Rio Tinto and BHP to achieve safer, more adaptive, and cost-efficient operations. These applications demonstrate the tangible value of ML in advancing sustainable and intelligent mining practices.

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[95]. Kurhade AS, Bhavani P, Patil SA, Kolhalkar NR, Chalapathi KS, Patil PA, Waware SY. Mitigating environmental impact: A study on the performance and emissions of a diesel engine fueled with biodiesel blend. Journal of Mines, Metals & Fuels. 2025 Apr 1;73(4):981-9. https://doi.org/10.18311/jmmf/2025/47669

[96]. Kurhade AS, Amruth E, Joshi PS, Kondhalkar GE, Jadhav PA, Murali G, Mahajan RG, Waware SY. Enhancing Flat-Plate Solar Collector Efficiency: A Numerical Study. Journal of Mines, Metals & Fuels. 2025 Apr 1;73(4). https://doi.org/10.18311/jmmf/2025/48249

[97]. Chougule SM, Murali G, Kurhade AS. Failure Investigation of the Driving Shaft in an Industrial Paddle Mixer. Journal of Mines, Metals & Fuels. 2025 May 1;73(5). https://doi.org/10.18311/jmmf/2025/48627

[98]. Chougule SM, Murali G, Kurhade AS. Finite Element Analysis and Design Optimization of a Paddle Mixer Shaft. Journal of Mines, Metals & Fuels. 2025 May 1;73(5). https://doi.org/10.18311/jmmf/2025/48664

[99]. Patil Y, Tatiya M, Dharmadhikari DD, Shahakar M, Patil SK, Mahajan RG, Kurhade AS. The Role of AI in Reducing Environmental Impact in the Mining Sector. Journal of Mines, Metals & Fuels. 2025 May 1;73(5).

[100]. Waware SY, Ahire PP, Napate K, Biradar R, Patil SP, Kore SS, Kurhade AS. Advancements in Heat Transfer Enhancement using Perforated Twisted Tapes: A Comprehensive Review. Journal of Mines, Metals & Fuels. 2025 May 1;73(5). https://doi.org/10.18311/jmmf/2025/48438

[101]. Kurhade AS, Sugumaran S, Kolhalkar NR, Karad MM, Mahajan RG, Shinde NM, Dalvi SA, Waware SY. Thermal management of mobile devices via PCM. Journal of Mines, Metals & Fuels. 2025 May 1;73(5):1313-20. https://doi.org/10.18311/jmmf/2025/48437

[102]. Napte K, Kondhalkar GE, Patil SV, Kharat PV, Banarase SM, Kurhade AS, Waware SY. Recent Advances in Sustainable Concrete and Steel Alternatives for Marine Infrastructure. Sustainable Marine Structures. 2025 Jun 4:107-31. https://doi.org/10.36956/sms.v7i2.2072

[103]. Chougule SM, Murali G, Kurhade AS. Design and Analysis of Industrial Material Handling Systems using FEA and Dynamic Simulation Techniques: FEA AND SIMULATION-BASED DESIGN OF MATERIAL HANDLING SYSTEMS. Journal of Scientific & Industrial Research (JSIR). 2025 Jun 18;84(6):645-53. https://doi.org/10.56042/jsir.v84i6.17512

[104]. Kondhalkar VK, Kurhade AS. Optimized Placement of IC Chips for Enhanced Thermal Cooling: A Hybrid ANN-GA Approach in Numerical Heat Transfer.

[105]. Deshpande SV, Pawar RS, Keche AJ, Kurhade A. Real-Time Surface Finish Measurement of Stepped Holding Shaft by Automatic System. Journal of Advanced Manufacturing Systems. 2025 Feb 25:1-26. https://doi.org/10.1142/S0219686725500386